{"id":4127,"date":"2018-09-03T19:38:09","date_gmt":"2018-09-03T17:38:09","guid":{"rendered":"https:\/\/www.kde.cs.uni-kassel.de\/?page_id=4127"},"modified":"2022-09-29T10:34:46","modified_gmt":"2022-09-29T08:34:46","slug":"publications","status":"publish","type":"page","link":"https:\/\/www.kde.cs.uni-kassel.de\/en\/hanika\/publications","title":{"rendered":"publications"},"content":{"rendered":"<div id=\"trailimageid\"><img decoding=\"async\" id=\"ttimg\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/loading.gif\"><\/div> <h2>List of publications and preprints by <a href=\"https:\/\/www.kde.cs.uni-kassel.de\/hanika\">Tom Hanika<\/a><\/h2>\n \n <ul class=\"bibsonomycsl_publications\">\n<\/ul>\n<a class=\"bibsonomycsl_publications-headline-anchor \" name=\"jmp_2025\"><\/a><h3 class=\"bibsonomycsl_publications-headline\" style=\"font-size: 1.1em; font-weight: bold;\">2025<\/h3>\n<ul class=\"bibsonomycsl_publications\"><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/incollection.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Hille, T., Hanika, T.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">Incomplete Formal Contexts and Their Intrinsic Dimension<\/span>.<\/span> In: Cellier, P., Ganter, B., and Missaoui, R. (eds.) SpringerLink. pp. 342\u2013358. Springer, Cham, Switzerland (2025). https:\/\/doi.org\/10.1007\/978-3-032-03364-2_22.<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/dblp.uni-trier.de\/rec\/conf\/concepts\/HilleH25.html\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-68a8cf80b683dcbae5968b57759274f3\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-68a8cf80b683dcbae5968b57759274f3\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/dx.doi.org\/10.1007\/978-3-032-03364-2_22\" target=\"_blank\">DOI<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/68a8cf80b683dcbae5968b57759274f3\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-68a8cf80b683dcbae5968b57759274f3\"><p>@incollection{Hille2025Sep,<br\/>  address = {Cham, Switzerland},<br\/>  author = {Hille, Tobias and Hanika, Tom},<br\/>  booktitle = {Conceptual Knowledge Structures},<br\/>  editor = {Cellier, Peggy and Ganter, Bernhard and Missaoui, Rokia},<br\/>  journal = {SpringerLink},<br\/>  keywords = {itegpub},<br\/>  month = {09},<br\/>  pages = {342--358},<br\/>  publisher = {Springer},<br\/>  series = {Lecture Notes in Computer Science},<br\/>  title = {Incomplete Formal Contexts and Their Intrinsic Dimension},<br\/>  type = {Publication},<br\/>  volume = 15941,<br\/>  year = 2025<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-68a8cf80b683dcbae5968b57759274f3\"><p>%0 Book Section<br\/>%1 Hille2025Sep<br\/>%A Hille, Tobias<br\/>%A Hanika, Tom<br\/>%B Conceptual Knowledge Structures<br\/>%C Cham, Switzerland<br\/>%D 2025<br\/>%E Cellier, Peggy<br\/>%E Ganter, Bernhard<br\/>%E Missaoui, Rokia<br\/>%I Springer<br\/>%J SpringerLink<br\/>%P 342--358<br\/>%R 10.1007\/978-3-032-03364-2_22<br\/>%T Incomplete Formal Contexts and Their Intrinsic Dimension<br\/>%U https:\/\/dblp.uni-trier.de\/rec\/conf\/concepts\/HilleH25.html<br\/>%V 15941<br\/>%@ 978-3-032-03364-2<br\/><\/p><\/div><\/div><\/li><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/inproceedings.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Stubbemann, M., Hille, T., Hanika, T.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">Unsupervised Selection of Features by Their Resilience to the Curse of Dimensionality.<\/span><\/span> In: Braun, T., Paa\u00dfen, B., and Stolzenburg, F. (eds.) KI. pp. 161\u2013174. Springer (2025).<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_url\"><a href=\"http:\/\/dblp.uni-trier.de\/db\/conf\/ki\/ki2025.html#StubbemannHH25\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-97af07f500a68aca0114d1c0020b201b\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-97af07f500a68aca0114d1c0020b201b\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/97af07f500a68aca0114d1c0020b201b\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-97af07f500a68aca0114d1c0020b201b\"><p>@inproceedings{conf\/ki\/StubbemannHH25,<br\/>  author = {Stubbemann, Maximilian and Hille, Tobias and Hanika, Tom},<br\/>  booktitle = {KI},<br\/>  crossref = {conf\/ki\/2025},<br\/>  editor = {Braun, Tanya and Paa\u00dfen, Benjamin and Stolzenburg, Frieder},<br\/>  keywords = {itegpub},<br\/>  pages = {161-174},<br\/>  publisher = {Springer},<br\/>  series = {Lecture Notes in Computer Science},<br\/>  title = {Unsupervised Selection of Features by Their Resilience to the Curse of Dimensionality.},<br\/>  volume = 15956,<br\/>  year = 2025<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-97af07f500a68aca0114d1c0020b201b\"><p>%0 Conference Paper<br\/>%1 conf\/ki\/StubbemannHH25<br\/>%A Stubbemann, Maximilian<br\/>%A Hille, Tobias<br\/>%A Hanika, Tom<br\/>%B KI<br\/>%D 2025<br\/>%E Braun, Tanya<br\/>%E Paa\u00dfen, Benjamin<br\/>%E Stolzenburg, Frieder<br\/>%I Springer<br\/>%P 161-174<br\/>%T Unsupervised Selection of Features by Their Resilience to the Curse of Dimensionality.<br\/>%U http:\/\/dblp.uni-trier.de\/db\/conf\/ki\/ki2025.html#StubbemannHH25<br\/>%V 15956<br\/>%@ 978-3-032-02813-6<br\/><\/p><\/div><\/div><\/li><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/misc.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">de Portugal Mecke, D.C., Alyoussef, H., Stubbemann, M., Koloiarov, I., Hanika, T., Schmidt-Thieme, L.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">STADE: Standard Deviation as a Pruning Metric<\/span><\/span>, https:\/\/arxiv.org\/abs\/2503.22451, (2025).<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/arxiv.org\/abs\/2503.22451\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-1b15dca83b745781584df0d24d410145\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-1b15dca83b745781584df0d24d410145\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/1b15dca83b745781584df0d24d410145\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-1b15dca83b745781584df0d24d410145\"><p>@misc{mecke2025stadestandarddeviationpruning,<br\/>  author = {de Portugal Mecke, Diego Coello and Alyoussef, Haya and Stubbemann, Maximilian and Koloiarov, Ilia and Hanika, Tom and Schmidt-Thieme, Lars},<br\/>  keywords = {itegpub},<br\/>  title = {STADE: Standard Deviation as a Pruning Metric},<br\/>  year = 2025<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-1b15dca83b745781584df0d24d410145\"><p>%0 Generic<br\/>%1 mecke2025stadestandarddeviationpruning<br\/>%A de Portugal Mecke, Diego Coello<br\/>%A Alyoussef, Haya<br\/>%A Stubbemann, Maximilian<br\/>%A Koloiarov, Ilia<br\/>%A Hanika, Tom<br\/>%A Schmidt-Thieme, Lars<br\/>%D 2025<br\/>%T STADE: Standard Deviation as a Pruning Metric<br\/>%U https:\/\/arxiv.org\/abs\/2503.22451<br\/><\/p><\/div><\/div><\/li><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/inproceedings.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Hirth, J., Hanika, T.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">The Geometric Structure of Topic Models.<\/span><\/span> In: Cellier, P., Ganter, B., and Missaoui, R. (eds.) CONCEPTS. pp. 19\u201334. Springer (2025).<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_url\"><a href=\"http:\/\/dblp.uni-trier.de\/db\/conf\/concepts\/concepts2025.html#HirthH25\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-5a44b915173530788e3275222e5292f1\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-5a44b915173530788e3275222e5292f1\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/5a44b915173530788e3275222e5292f1\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-5a44b915173530788e3275222e5292f1\"><p>@inproceedings{conf\/concepts\/HirthH25,<br\/>  author = {Hirth, Johannes and Hanika, Tom},<br\/>  booktitle = {CONCEPTS},<br\/>  crossref = {conf\/concepts\/2025},<br\/>  editor = {Cellier, Peggy and Ganter, Bernhard and Missaoui, Rokia},<br\/>  keywords = {itegpub},<br\/>  pages = {19-34},<br\/>  publisher = {Springer},<br\/>  series = {Lecture Notes in Computer Science},<br\/>  title = {The Geometric Structure of Topic Models.},<br\/>  volume = 15941,<br\/>  year = 2025<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-5a44b915173530788e3275222e5292f1\"><p>%0 Conference Paper<br\/>%1 conf\/concepts\/HirthH25<br\/>%A Hirth, Johannes<br\/>%A Hanika, Tom<br\/>%B CONCEPTS<br\/>%D 2025<br\/>%E Cellier, Peggy<br\/>%E Ganter, Bernhard<br\/>%E Missaoui, Rokia<br\/>%I Springer<br\/>%P 19-34<br\/>%T The Geometric Structure of Topic Models.<br\/>%U http:\/\/dblp.uni-trier.de\/db\/conf\/concepts\/concepts2025.html#HirthH25<br\/>%V 15941<br\/>%@ 978-3-032-03364-2<br\/><\/p><\/div><\/div><\/li>\n<\/ul>\n<a class=\"bibsonomycsl_publications-headline-anchor \" name=\"jmp_2024\"><\/a><h3 class=\"bibsonomycsl_publications-headline\" style=\"font-size: 1.1em; font-weight: bold;\">2024<\/h3>\n<ul class=\"bibsonomycsl_publications\"><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/article.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Hirth, J., Horn, V., Stumme, G., Hanika, T.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">Ordinal motifs in lattices<\/span>.<\/span> Information Sciences. 659, 120009 (2024). https:\/\/doi.org\/https:\/\/doi.org\/10.1016\/j.ins.2023.120009.<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0020025523015943\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-cfce342df6fc34ebd60a9dbbddb0e540\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-cfce342df6fc34ebd60a9dbbddb0e540\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/doi.org\/10.1016\/j.ins.2023.120009\" target=\"_blank\">DOI<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/cfce342df6fc34ebd60a9dbbddb0e540\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-cfce342df6fc34ebd60a9dbbddb0e540\"><p>@article{HIRTH2024120009,<br\/>  author = {Hirth, Johannes and Horn, Viktoria and Stumme, Gerd and Hanika, Tom},<br\/>  journal = {Information Sciences},<br\/>  keywords = {itegpub},<br\/>  pages = 120009,<br\/>  title = {Ordinal motifs in lattices},<br\/>  volume = 659,<br\/>  year = 2024<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-cfce342df6fc34ebd60a9dbbddb0e540\"><p>%0 Journal Article<br\/>%1 HIRTH2024120009<br\/>%A Hirth, Johannes<br\/>%A Horn, Viktoria<br\/>%A Stumme, Gerd<br\/>%A Hanika, Tom<br\/>%D 2024<br\/>%J Information Sciences<br\/>%P 120009<br\/>%R https:\/\/doi.org\/10.1016\/j.ins.2023.120009<br\/>%T Ordinal motifs in lattices<br\/>%U https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0020025523015943<br\/>%V 659<br\/><\/p><\/div><\/div><\/li><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/inproceedings.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Hanika, T., J\u00e4schke, R.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">A Repository for Formal Contexts<\/span>.<\/span> In: Proceedings of the 1st International Joint Conference on Conceptual Knowledge Structures (2024).<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_export bibsonomycsl_abstract\"><a rel=\"abs-9cd9667ebadfba3a36f95fd901e32724\"  href=\"#\">Abstract<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/arxiv.org\/abs\/2404.04344\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-9cd9667ebadfba3a36f95fd901e32724\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-9cd9667ebadfba3a36f95fd901e32724\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/9cd9667ebadfba3a36f95fd901e32724\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_abstract\" style=\"display:none;\" id=\"abs-9cd9667ebadfba3a36f95fd901e32724\">Data is always at the center of the theoretical development and investigation of the applicability of formal concept analysis. It is therefore not surprising that a large number of data sets are repeatedly used in scholarly articles and software tools, acting as de facto standard data sets. However, the distribution of the data sets poses a problem for the sustainable development of the research field. There is a lack of a central location that provides and describes FCA data sets and links them to already known analysis results. This article analyses the current state of the dissemination of FCA data sets, presents the requirements for a central FCA repository, and highlights the challenges for this.<\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-9cd9667ebadfba3a36f95fd901e32724\"><p>@inproceedings{hanika2024repository,<br\/>  abstract = {Data is always at the center of the theoretical development and investigation of the applicability of formal concept analysis. It is therefore not surprising that a large number of data sets are repeatedly used in scholarly articles and software tools, acting as de facto standard data sets. However, the distribution of the data sets poses a problem for the sustainable development of the research field. There is a lack of a central location that provides and describes FCA data sets and links them to already known analysis results. This article analyses the current state of the dissemination of FCA data sets, presents the requirements for a central FCA repository, and highlights the challenges for this.},<br\/>  author = {Hanika, Tom and J\u00e4schke, Robert},<br\/>  booktitle = {Proceedings of the 1st International Joint Conference on Conceptual Knowledge Structures},<br\/>  keywords = {repository},<br\/>  title = {A Repository for Formal Contexts},<br\/>  year = 2024<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-9cd9667ebadfba3a36f95fd901e32724\"><p>%0 Conference Paper<br\/>%1 hanika2024repository<br\/>%A Hanika, Tom<br\/>%A J\u00e4schke, Robert<br\/>%B Proceedings of the 1st International Joint Conference on Conceptual Knowledge Structures<br\/>%D 2024<br\/>%T A Repository for Formal Contexts<br\/>%U https:\/\/arxiv.org\/abs\/2404.04344<br\/>%X Data is always at the center of the theoretical development and investigation of the applicability of formal concept analysis. It is therefore not surprising that a large number of data sets are repeatedly used in scholarly articles and software tools, acting as de facto standard data sets. However, the distribution of the data sets poses a problem for the sustainable development of the research field. There is a lack of a central location that provides and describes FCA data sets and links them to already known analysis results. This article analyses the current state of the dissemination of FCA data sets, presents the requirements for a central FCA repository, and highlights the challenges for this.<br\/><\/p><\/div><\/div><\/li><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/preprint.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Hirth, J., Hanika, T.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">The Geometric Structure of Topic Models<\/span><\/span>, (2024).<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_export bibsonomycsl_abstract\"><a rel=\"abs-2d7d326826df7ef88a62c4330a1d22dd\"  href=\"#\">Abstract<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-2d7d326826df7ef88a62c4330a1d22dd\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-2d7d326826df7ef88a62c4330a1d22dd\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/2d7d326826df7ef88a62c4330a1d22dd\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_abstract\" style=\"display:none;\" id=\"abs-2d7d326826df7ef88a62c4330a1d22dd\">Topic models are a popular tool for clustering and analyzing textual data. They allow texts to be classified on the basis of their affiliation to the previously calculated topics. Despite their widespread use in research and application, an in-depth analysis of topic models is still an open research topic. State-of-the-art methods for interpreting topic models are based on simple visualizations, such as similarity matrices, top-term lists or embeddings, which are limited to a maximum of three dimensions. In this paper, we propose an incidence-geometric method for deriving an ordinal structure from flat topic models, such as non-negative matrix factorization. These enable the analysis of the topic model in a higher (order) dimension and the possibility of extracting conceptual relationships between several topics at once. Due to the use of conceptual scaling, our approach does not introduce any artificial topical relationships, such as artifacts of feature compression. Based on our findings, we present a new visualization paradigm for concept hierarchies based on ordinal motifs. These allow for a top-down view on topic spaces. We introduce and demonstrate the applicability of our approach based on a topic model derived from a corpus of scientific papers taken from 32 top machine learning venues.<\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-2d7d326826df7ef88a62c4330a1d22dd\"><p>@preprint{hirth2024geometric,<br\/>  abstract = {Topic models are a popular tool for clustering and analyzing textual data. They allow texts to be classified on the basis of their affiliation to the previously calculated topics. Despite their widespread use in research and application, an in-depth analysis of topic models is still an open research topic. State-of-the-art methods for interpreting topic models are based on simple visualizations, such as similarity matrices, top-term lists or embeddings, which are limited to a maximum of three dimensions. In this paper, we propose an incidence-geometric method for deriving an ordinal structure from flat topic models, such as non-negative matrix factorization. These enable the analysis of the topic model in a higher (order) dimension and the possibility of extracting conceptual relationships between several topics at once. Due to the use of conceptual scaling, our approach does not introduce any artificial topical relationships, such as artifacts of feature compression. Based on our findings, we present a new visualization paradigm for concept hierarchies based on ordinal motifs. These allow for a top-down view on topic spaces. We introduce and demonstrate the applicability of our approach based on a topic model derived from a corpus of scientific papers taken from 32 top machine learning venues.},<br\/>  author = {Hirth, Johannes and Hanika, Tom},<br\/>  keywords = {kde},<br\/>  title = {The Geometric Structure of Topic Models},<br\/>  year = 2024<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-2d7d326826df7ef88a62c4330a1d22dd\"><p>%0 Generic<br\/>%1 hirth2024geometric<br\/>%A Hirth, Johannes<br\/>%A Hanika, Tom<br\/>%D 2024<br\/>%T The Geometric Structure of Topic Models<br\/>%X Topic models are a popular tool for clustering and analyzing textual data. They allow texts to be classified on the basis of their affiliation to the previously calculated topics. Despite their widespread use in research and application, an in-depth analysis of topic models is still an open research topic. State-of-the-art methods for interpreting topic models are based on simple visualizations, such as similarity matrices, top-term lists or embeddings, which are limited to a maximum of three dimensions. In this paper, we propose an incidence-geometric method for deriving an ordinal structure from flat topic models, such as non-negative matrix factorization. These enable the analysis of the topic model in a higher (order) dimension and the possibility of extracting conceptual relationships between several topics at once. Due to the use of conceptual scaling, our approach does not introduce any artificial topical relationships, such as artifacts of feature compression. Based on our findings, we present a new visualization paradigm for concept hierarchies based on ordinal motifs. These allow for a top-down view on topic spaces. We introduce and demonstrate the applicability of our approach based on a topic model derived from a corpus of scientific papers taken from 32 top machine learning venues.<br\/><\/p><\/div><\/div><\/li><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/article.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Hille, T., Stubbemann, M., Hanika, T.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">Reproducibility and Geometric Intrinsic Dimensionality: An Investigation on Graph Neural Network Research.<\/span><\/span> Transactions on Machine Learning Research. (2024).<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/openreview.net\/forum?id=CtEGxIqtud\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-18db05755dfccccb1d71888db7e18926\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-18db05755dfccccb1d71888db7e18926\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/18db05755dfccccb1d71888db7e18926\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-18db05755dfccccb1d71888db7e18926\"><p>@article{hille2024reproducibility,<br\/>  author = {Hille, Tobias and Stubbemann, Maximilian and Hanika, Tom},<br\/>  journal = {Transactions on Machine Learning Research},<br\/>  keywords = {itegpub},<br\/>  note = {Reproducibility Certification},<br\/>  title = {Reproducibility and Geometric Intrinsic Dimensionality: An Investigation on Graph Neural Network Research.},<br\/>  year = 2024<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-18db05755dfccccb1d71888db7e18926\"><p>%0 Journal Article<br\/>%1 hille2024reproducibility<br\/>%A Hille, Tobias<br\/>%A Stubbemann, Maximilian<br\/>%A Hanika, Tom<br\/>%D 2024<br\/>%J Transactions on Machine Learning Research<br\/>%T Reproducibility and Geometric Intrinsic Dimensionality: An Investigation on Graph Neural Network Research.<br\/>%U https:\/\/openreview.net\/forum?id=CtEGxIqtud<br\/><\/p><\/div><\/div><\/li><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/inproceedings.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Ganter, B., Hanika, T., Hirth, J., Obiedkov, S.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">Collaborative Hybrid Human {AI} Learning through Conceptual Exploration<\/span>.<\/span> In: Ericson, P., Khairova, N., and Vos, M.D. (eds.) Proceedings of the Workshops at the Third International Conference on Hybrid Human-Artificial Intelligence co-located with (HHAI) 2024), Malm\u00f6, Sweden, June 10-11, 2024. pp. 1\u20138. CEUR-WS.org (2024).<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/ceur-ws.org\/Vol-3825\/tutorial.pdf\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-5850bd6b4c1c6946a58995605ed1e6d0\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-5850bd6b4c1c6946a58995605ed1e6d0\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/5850bd6b4c1c6946a58995605ed1e6d0\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-5850bd6b4c1c6946a58995605ed1e6d0\"><p>@inproceedings{DBLP:conf\/hhai\/GanterHHO24,<br\/>  author = {Ganter, Bernhard and Hanika, Tom and Hirth, Johannes and Obiedkov, Sergei},<br\/>  booktitle = {Proceedings of the Workshops at the Third International Conference on Hybrid Human-Artificial Intelligence co-located with (HHAI) 2024), Malm\u00f6, Sweden, June 10-11, 2024},<br\/>  editor = {Ericson, Petter and Khairova, Nina and Vos, Marina De},<br\/>  keywords = {itegpub},<br\/>  pages = {1--8},<br\/>  publisher = {CEUR-WS.org},<br\/>  series = {{CEUR} Workshop Proceedings},<br\/>  title = {Collaborative Hybrid Human {AI} Learning through Conceptual Exploration},<br\/>  volume = 3825,<br\/>  year = 2024<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-5850bd6b4c1c6946a58995605ed1e6d0\"><p>%0 Conference Paper<br\/>%1 DBLP:conf\/hhai\/GanterHHO24<br\/>%A Ganter, Bernhard<br\/>%A Hanika, Tom<br\/>%A Hirth, Johannes<br\/>%A Obiedkov, Sergei<br\/>%B Proceedings of the Workshops at the Third International Conference on Hybrid Human-Artificial Intelligence co-located with (HHAI) 2024), Malm\u00f6, Sweden, June 10-11, 2024<br\/>%D 2024<br\/>%E Ericson, Petter<br\/>%E Khairova, Nina<br\/>%E Vos, Marina De<br\/>%I CEUR-WS.org<br\/>%P 1--8<br\/>%T Collaborative Hybrid Human {AI} Learning through Conceptual Exploration<br\/>%U https:\/\/ceur-ws.org\/Vol-3825\/tutorial.pdf<br\/>%V 3825<br\/><\/p><\/div><\/div><\/li><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/article.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Budde, K.B., Rellstab, C., Heuertz, M., Gugerli, F., Hanika, T., Verd\u00fa, M., Pausas, J.G., Gonz\u00e1lez-Mart\u00ednez, S.C.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">Divergent selection in a Mediterranean pine on local spatial scales<\/span>.<\/span> Journal of Ecology. 112, (2024). https:\/\/doi.org\/https:\/\/doi.org\/10.1111\/1365-2745.14231.<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_export bibsonomycsl_abstract\"><a rel=\"abs-64cdb512638b967b2d03a82ad77bcbfe\"  href=\"#\">Abstract<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/besjournals.onlinelibrary.wiley.com\/doi\/abs\/10.1111\/1365-2745.14231\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-64cdb512638b967b2d03a82ad77bcbfe\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-64cdb512638b967b2d03a82ad77bcbfe\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/doi.org\/10.1111\/1365-2745.14231\" target=\"_blank\">DOI<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/64cdb512638b967b2d03a82ad77bcbfe\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_abstract\" style=\"display:none;\" id=\"abs-64cdb512638b967b2d03a82ad77bcbfe\">Abstract The effects of selection on an organism's genome are hard to detect on small spatial scales, as gene flow can swamp signatures of local adaptation. Therefore, most genome scans to detect signatures of environmental selection are performed on large spatial scales; however, divergent selection on the local scale (e.g. between contrasting soil conditions) has also been demonstrated, in particular for herbaceous plants. Here, we hypothesised that in topographically complex landscapes, microenvironment variability is strong enough to leave a selective footprint in the genomes of long-lived organisms. To test this, we investigated paired south- versus north-facing Pinus pinaster stands on the local scale, with trees growing in close vicinity (\u2264820\u2009m distance between paired south- and north-facing stands), in a Mediterranean mountain area. While trees on north-facing slopes experience less radiation, trees on south-facing slopes suffer from especially harsh conditions, particularly during the dry summer season. Two outlier analyses consistently revealed five putatively adaptive loci (out of 4034), in candidate genes two of which encoded non-synonymous substitutions. Additionally, one locus showed consistent allele frequency differences in all three stand pairs indicating divergent selection despite high gene flow on the local scale. Permutation tests demonstrated that our findings were robust. Functional annotation of these candidate genes revealed biological functions related to abiotic stress response, such as water availability, in other plant species. Synthesis. Our study highlights how divergent selection in heterogeneous microenvironments shapes and maintains the functional genetic variation within populations of long-lived forest tree species, being the first to focus on adaptive genetic divergence between south- and north-facing slopes within continuous forest stands. This is especially relevant in the current context of climate change, as this variation is at the base of plant population responses to future climate.<\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-64cdb512638b967b2d03a82ad77bcbfe\"><p>@article{https:\/\/doi.org\/10.1111\/1365-2745.14231,<br\/>  abstract = {Abstract The effects of selection on an organism's genome are hard to detect on small spatial scales, as gene flow can swamp signatures of local adaptation. Therefore, most genome scans to detect signatures of environmental selection are performed on large spatial scales; however, divergent selection on the local scale (e.g. between contrasting soil conditions) has also been demonstrated, in particular for herbaceous plants. Here, we hypothesised that in topographically complex landscapes, microenvironment variability is strong enough to leave a selective footprint in the genomes of long-lived organisms. To test this, we investigated paired south- versus north-facing Pinus pinaster stands on the local scale, with trees growing in close vicinity (\u2264820\u2009m distance between paired south- and north-facing stands), in a Mediterranean mountain area. While trees on north-facing slopes experience less radiation, trees on south-facing slopes suffer from especially harsh conditions, particularly during the dry summer season. Two outlier analyses consistently revealed five putatively adaptive loci (out of 4034), in candidate genes two of which encoded non-synonymous substitutions. Additionally, one locus showed consistent allele frequency differences in all three stand pairs indicating divergent selection despite high gene flow on the local scale. Permutation tests demonstrated that our findings were robust. Functional annotation of these candidate genes revealed biological functions related to abiotic stress response, such as water availability, in other plant species. Synthesis. Our study highlights how divergent selection in heterogeneous microenvironments shapes and maintains the functional genetic variation within populations of long-lived forest tree species, being the first to focus on adaptive genetic divergence between south- and north-facing slopes within continuous forest stands. This is especially relevant in the current context of climate change, as this variation is at the base of plant population responses to future climate.},<br\/>  author = {Budde, Katharina B. and Rellstab, Christian and Heuertz, Myriam and Gugerli, Felix and Hanika, Tom and Verd\u00fa, Miguel and Pausas, Juli G. and Gonz\u00e1lez-Mart\u00ednez, Santiago C.},<br\/>  journal = {Journal of Ecology},<br\/>  keywords = {itegpub},<br\/>  number = 2,<br\/>  title = {Divergent selection in a Mediterranean pine on local spatial scales},<br\/>  volume = 112,<br\/>  year = 2024<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-64cdb512638b967b2d03a82ad77bcbfe\"><p>%0 Journal Article<br\/>%1 https:\/\/doi.org\/10.1111\/1365-2745.14231<br\/>%A Budde, Katharina B.<br\/>%A Rellstab, Christian<br\/>%A Heuertz, Myriam<br\/>%A Gugerli, Felix<br\/>%A Hanika, Tom<br\/>%A Verd\u00fa, Miguel<br\/>%A Pausas, Juli G.<br\/>%A Gonz\u00e1lez-Mart\u00ednez, Santiago C.<br\/>%D 2024<br\/>%J Journal of Ecology<br\/>%N 2<br\/>%R https:\/\/doi.org\/10.1111\/1365-2745.14231<br\/>%T Divergent selection in a Mediterranean pine on local spatial scales<br\/>%U https:\/\/besjournals.onlinelibrary.wiley.com\/doi\/abs\/10.1111\/1365-2745.14231<br\/>%V 112<br\/>%X Abstract The effects of selection on an organism's genome are hard to detect on small spatial scales, as gene flow can swamp signatures of local adaptation. Therefore, most genome scans to detect signatures of environmental selection are performed on large spatial scales; however, divergent selection on the local scale (e.g. between contrasting soil conditions) has also been demonstrated, in particular for herbaceous plants. Here, we hypothesised that in topographically complex landscapes, microenvironment variability is strong enough to leave a selective footprint in the genomes of long-lived organisms. To test this, we investigated paired south- versus north-facing Pinus pinaster stands on the local scale, with trees growing in close vicinity (\u2264820\u2009m distance between paired south- and north-facing stands), in a Mediterranean mountain area. While trees on north-facing slopes experience less radiation, trees on south-facing slopes suffer from especially harsh conditions, particularly during the dry summer season. Two outlier analyses consistently revealed five putatively adaptive loci (out of 4034), in candidate genes two of which encoded non-synonymous substitutions. Additionally, one locus showed consistent allele frequency differences in all three stand pairs indicating divergent selection despite high gene flow on the local scale. Permutation tests demonstrated that our findings were robust. Functional annotation of these candidate genes revealed biological functions related to abiotic stress response, such as water availability, in other plant species. Synthesis. Our study highlights how divergent selection in heterogeneous microenvironments shapes and maintains the functional genetic variation within populations of long-lived forest tree species, being the first to focus on adaptive genetic divergence between south- and north-facing slopes within continuous forest stands. This is especially relevant in the current context of climate change, as this variation is at the base of plant population responses to future climate.<br\/><\/p><\/div><\/div><\/li><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/inproceedings.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Hanika, T., Hille, T.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">What is the Intrinsic Dimension of Your Binary Data? - and How to Compute it Quickly<\/span>.<\/span> In: Cabrera, I.P., Ferr{{\u00e9}}, S., and Obiedkov, S.A. (eds.) Conceptual Knowledge Structures - First International Joint Conference, {CONCEPTS} 2024, C{{\u00e1}}diz, Spain, September 9-13, 2024, Proceedings. pp. 97\u2013112. Springer (2024). https:\/\/doi.org\/10.1007\/978-3-031-67868-4\\_7.<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/doi.org\/10.1007\/978-3-031-67868-4\\_7\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-7d80701f6e46efb6c3fe036260c3ac38\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-7d80701f6e46efb6c3fe036260c3ac38\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/dx.doi.org\/10.1007\/978-3-031-67868-4\\_7\" target=\"_blank\">DOI<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/7d80701f6e46efb6c3fe036260c3ac38\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-7d80701f6e46efb6c3fe036260c3ac38\"><p>@inproceedings{DBLP:conf\/concepts\/HanikaH24,<br\/>  author = {Hanika, Tom and Hille, Tobias},<br\/>  booktitle = {Conceptual Knowledge Structures - First International Joint Conference, {CONCEPTS} 2024, C{{\u00e1}}diz, Spain, September 9-13, 2024, Proceedings},<br\/>  editor = {Cabrera, Inma P. and Ferr{{\u00e9}}, S{{\u00e9}}bastien and Obiedkov, Sergei A.},<br\/>  keywords = {itegpub},<br\/>  pages = {97--112},<br\/>  publisher = {Springer},<br\/>  series = {Lecture Notes in Computer Science},<br\/>  title = {What is the Intrinsic Dimension of Your Binary Data? - and How to Compute it Quickly},<br\/>  volume = 14914,<br\/>  year = 2024<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-7d80701f6e46efb6c3fe036260c3ac38\"><p>%0 Conference Paper<br\/>%1 DBLP:conf\/concepts\/HanikaH24<br\/>%A Hanika, Tom<br\/>%A Hille, Tobias<br\/>%B Conceptual Knowledge Structures - First International Joint Conference, {CONCEPTS} 2024, C{{\u00e1}}diz, Spain, September 9-13, 2024, Proceedings<br\/>%D 2024<br\/>%E Cabrera, Inma P.<br\/>%E Ferr{{\u00e9}}, S{{\u00e9}}bastien<br\/>%E Obiedkov, Sergei A.<br\/>%I Springer<br\/>%P 97--112<br\/>%R 10.1007\/978-3-031-67868-4\\_7<br\/>%T What is the Intrinsic Dimension of Your Binary Data? - and How to Compute it Quickly<br\/>%U https:\/\/doi.org\/10.1007\/978-3-031-67868-4\\_7<br\/>%V 14914<br\/><\/p><\/div><\/div><\/li>\n<\/ul>\n<a class=\"bibsonomycsl_publications-headline-anchor \" name=\"jmp_2023\"><\/a><h3 class=\"bibsonomycsl_publications-headline\" style=\"font-size: 1.1em; font-weight: bold;\">2023<\/h3>\n<ul class=\"bibsonomycsl_publications\"><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/inproceedings.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Ganter, B., Hanika, T., Hirth, J.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">Scaling Dimension<\/span>.<\/span> In: D\u00fcrrschnabel, D. and L\u00f3pez-Rodr\u00edguez, D. (eds.) Formal Concept Analysis - 17th International Conference, {ICFCA} 2023, Kassel, Germany, July 17-21, 2023, Proceedings. pp. 64\u201377. Springer (2023). https:\/\/doi.org\/10.1007\/978-3-031-35949-1\\_5.<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/doi.org\/10.1007\/978-3-031-35949-1\\_5\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-ae364c1012bb099c906b24ecdc7f688d\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-ae364c1012bb099c906b24ecdc7f688d\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/dx.doi.org\/10.1007\/978-3-031-35949-1\\_5\" target=\"_blank\">DOI<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/ae364c1012bb099c906b24ecdc7f688d\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-ae364c1012bb099c906b24ecdc7f688d\"><p>@inproceedings{DBLP:conf\/icfca\/GanterHH23,<br\/>  author = {Ganter, Bernhard and Hanika, Tom and Hirth, Johannes},<br\/>  booktitle = {Formal Concept Analysis - 17th International Conference, {ICFCA} 2023, Kassel, Germany, July 17-21, 2023, Proceedings},<br\/>  editor = {D\u00fcrrschnabel, Dominik and L\u00f3pez-Rodr\u00edguez, Domingo},<br\/>  keywords = {itegpub},<br\/>  pages = {64--77},<br\/>  publisher = {Springer},<br\/>  series = {Lecture Notes in Computer Science},<br\/>  title = {Scaling Dimension},<br\/>  volume = 13934,<br\/>  year = 2023<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-ae364c1012bb099c906b24ecdc7f688d\"><p>%0 Conference Paper<br\/>%1 DBLP:conf\/icfca\/GanterHH23<br\/>%A Ganter, Bernhard<br\/>%A Hanika, Tom<br\/>%A Hirth, Johannes<br\/>%B Formal Concept Analysis - 17th International Conference, {ICFCA} 2023, Kassel, Germany, July 17-21, 2023, Proceedings<br\/>%D 2023<br\/>%E D\u00fcrrschnabel, Dominik<br\/>%E L\u00f3pez-Rodr\u00edguez, Domingo<br\/>%I Springer<br\/>%P 64--77<br\/>%R 10.1007\/978-3-031-35949-1\\_5<br\/>%T Scaling Dimension<br\/>%U https:\/\/doi.org\/10.1007\/978-3-031-35949-1\\_5<br\/>%V 13934<br\/><\/p><\/div><\/div><\/li><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/article.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">D\u00fcrrschnabel, D., Hanika, T., Stumme, G.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">Drawing Order Diagrams Through Two-Dimension Extension<\/span>.<\/span> Journal of Graph Algorithms and Applications. 27, 783\u2013802 (2023). https:\/\/doi.org\/10.7155\/jgaa.00645.<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_url\"><a href=\"http:\/\/dx.doi.org\/10.7155\/jgaa.00645\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-fd95bbf455a80e1e2c5995e57496ce44\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-fd95bbf455a80e1e2c5995e57496ce44\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/dx.doi.org\/10.7155\/jgaa.00645\" target=\"_blank\">DOI<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/fd95bbf455a80e1e2c5995e57496ce44\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-fd95bbf455a80e1e2c5995e57496ce44\"><p>@article{drrschnabel2023drawing,<br\/>  author = {D\u00fcrrschnabel, Dominik and Hanika, Tom and Stumme, Gerd},<br\/>  journal = {Journal of Graph Algorithms and Applications},<br\/>  keywords = {itegpub},<br\/>  number = 9,<br\/>  pages = {783\u2013802},<br\/>  publisher = {Journal of Graph Algorithms and Applications},<br\/>  title = {Drawing Order Diagrams Through Two-Dimension Extension},<br\/>  volume = 27,<br\/>  year = 2023<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-fd95bbf455a80e1e2c5995e57496ce44\"><p>%0 Journal Article<br\/>%1 drrschnabel2023drawing<br\/>%A D\u00fcrrschnabel, Dominik<br\/>%A Hanika, Tom<br\/>%A Stumme, Gerd<br\/>%D 2023<br\/>%I Journal of Graph Algorithms and Applications<br\/>%J Journal of Graph Algorithms and Applications<br\/>%N 9<br\/>%P 783\u2013802<br\/>%R 10.7155\/jgaa.00645<br\/>%T Drawing Order Diagrams Through Two-Dimension Extension<br\/>%U http:\/\/dx.doi.org\/10.7155\/jgaa.00645<br\/>%V 27<br\/><\/p><\/div><\/div><\/li><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border\"><img decoding=\"async\" onmouseover=\"javascript:showtrail('https:\/\/www.kde.cs.uni-kassel.de\/en\/hanika\/publications?action=preview&userName=tomhanika&intraHash=2a81e1a16f19a49828043bca146c41c8&fileName=TGDK.1.1.6.pdf&size=LARGE')\" onmouseout=\"javascript:hidetrail()\" class=\"bibsonomycsl_preview\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/en\/hanika\/publications?action=preview&userName=tomhanika&intraHash=2a81e1a16f19a49828043bca146c41c8&fileName=TGDK.1.1.6.pdf&size=SMALL&doc%5B\u0000GuzzleHttp\\Psr7\\Stream\u0000stream%5D=Resource id #58&doc%5B\u0000GuzzleHttp\\Psr7\\Stream\u0000seekable%5D=1&doc%5B\u0000GuzzleHttp\\Psr7\\Stream\u0000readable%5D=1&doc%5B\u0000GuzzleHttp\\Psr7\\Stream\u0000writable%5D=1&doc%5B\u0000GuzzleHttp\\Psr7\\Stream\u0000uri%5D=php:\/\/temp&\" \/><\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Stumme, G., D\u00fcrrschnabel, D., Hanika, T.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">Towards Ordinal Data Science<\/span>.<\/span> Transactions on Graph Data and Knowledge. 1, 6:1\u20136:39 (2023). https:\/\/doi.org\/10.4230\/TGDK.1.1.6.<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/doi.org\/10.4230\/TGDK.1.1.6\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-2a81e1a16f19a49828043bca146c41c8\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-2a81e1a16f19a49828043bca146c41c8\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/dx.doi.org\/10.4230\/TGDK.1.1.6\" target=\"_blank\">DOI<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/2a81e1a16f19a49828043bca146c41c8\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><span class=\"bibsonomycsl_download\"><a href=\"https:\/\/www.kde.cs.uni-kassel.de\/en\/hanika\/publications?action=download&userName=tomhanika&intraHash=2a81e1a16f19a49828043bca146c41c8&fileName=TGDK.1.1.6.pdf\" target=\"_blank\">Download<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-2a81e1a16f19a49828043bca146c41c8\"><p>@article{DBLP:journals\/tgdk\/StummeDH23,<br\/>  author = {Stumme, Gerd and D\u00fcrrschnabel, Dominik and Hanika, Tom},<br\/>  journal = {Transactions on Graph Data and Knowledge},<br\/>  keywords = {itegpub},<br\/>  number = 1,<br\/>  pages = {6:1--6:39},<br\/>  title = {Towards Ordinal Data Science},<br\/>  volume = 1,<br\/>  year = 2023<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-2a81e1a16f19a49828043bca146c41c8\"><p>%0 Journal Article<br\/>%1 DBLP:journals\/tgdk\/StummeDH23<br\/>%A Stumme, Gerd<br\/>%A D\u00fcrrschnabel, Dominik<br\/>%A Hanika, Tom<br\/>%D 2023<br\/>%J Transactions on Graph Data and Knowledge<br\/>%N 1<br\/>%P 6:1--6:39<br\/>%R 10.4230\/TGDK.1.1.6<br\/>%T Towards Ordinal Data Science<br\/>%U https:\/\/doi.org\/10.4230\/TGDK.1.1.6<br\/>%V 1<br\/><\/p><\/div><\/div><\/li><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/article.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Hanika, T., Hirth, J.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">Conceptual views on tree ensemble classifiers<\/span>.<\/span> International Journal of Approximate Reasoning. 159, 108930 (2023). https:\/\/doi.org\/https:\/\/doi.org\/10.1016\/j.ijar.2023.108930.<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_export bibsonomycsl_abstract\"><a rel=\"abs-3709ed3ff9ac089641070c1aac3cb02d\"  href=\"#\">Abstract<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0888613X23000610\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-3709ed3ff9ac089641070c1aac3cb02d\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-3709ed3ff9ac089641070c1aac3cb02d\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/doi.org\/10.1016\/j.ijar.2023.108930\" target=\"_blank\">DOI<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/3709ed3ff9ac089641070c1aac3cb02d\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_abstract\" style=\"display:none;\" id=\"abs-3709ed3ff9ac089641070c1aac3cb02d\">Random Forests and related tree-based methods are popular for supervised learning from table based data. Apart from their ease of parallelization, their classification performance is also superior. However, this performance, especially parallelizability, is offset by the loss of explainability. Statistical methods are often used to compensate for this disadvantage. Yet, their ability for local explanations, and in particular for global explanations, is limited. In the present work we propose an algebraic method, rooted in lattice theory, for the (global) explanation of tree ensembles. In detail, we introduce two novel conceptual views on tree ensemble classifiers and demonstrate their explanatory capabilities on Random Forests that were trained with standard parameters.<\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-3709ed3ff9ac089641070c1aac3cb02d\"><p>@article{HANIKA2023108930,<br\/>  abstract = {Random Forests and related tree-based methods are popular for supervised learning from table based data. Apart from their ease of parallelization, their classification performance is also superior. However, this performance, especially parallelizability, is offset by the loss of explainability. Statistical methods are often used to compensate for this disadvantage. Yet, their ability for local explanations, and in particular for global explanations, is limited. In the present work we propose an algebraic method, rooted in lattice theory, for the (global) explanation of tree ensembles. In detail, we introduce two novel conceptual views on tree ensemble classifiers and demonstrate their explanatory capabilities on Random Forests that were trained with standard parameters.},<br\/>  author = {Hanika, Tom and Hirth, Johannes},<br\/>  journal = {International Journal of Approximate Reasoning},<br\/>  keywords = {xai},<br\/>  pages = 108930,<br\/>  title = {Conceptual views on tree ensemble classifiers},<br\/>  volume = 159,<br\/>  year = 2023<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-3709ed3ff9ac089641070c1aac3cb02d\"><p>%0 Journal Article<br\/>%1 HANIKA2023108930<br\/>%A Hanika, Tom<br\/>%A Hirth, Johannes<br\/>%D 2023<br\/>%J International Journal of Approximate Reasoning<br\/>%P 108930<br\/>%R https:\/\/doi.org\/10.1016\/j.ijar.2023.108930<br\/>%T Conceptual views on tree ensemble classifiers<br\/>%U https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0888613X23000610<br\/>%V 159<br\/>%X Random Forests and related tree-based methods are popular for supervised learning from table based data. Apart from their ease of parallelization, their classification performance is also superior. However, this performance, especially parallelizability, is offset by the loss of explainability. Statistical methods are often used to compensate for this disadvantage. Yet, their ability for local explanations, and in particular for global explanations, is limited. In the present work we propose an algebraic method, rooted in lattice theory, for the (global) explanation of tree ensembles. In detail, we introduce two novel conceptual views on tree ensemble classifiers and demonstrate their explanatory capabilities on Random Forests that were trained with standard parameters.<br\/><\/p><\/div><\/div><\/li><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/article.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Stubbemann, M., Hille, T., Hanika, T.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">Selecting Features by their Resilience to the Curse of Dimensionality<\/span>.<\/span> (2023).<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-226d9608a2279971502570f1c18c5fa4\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-226d9608a2279971502570f1c18c5fa4\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/226d9608a2279971502570f1c18c5fa4\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-226d9608a2279971502570f1c18c5fa4\"><p>@article{stubbemann2023selecting,<br\/>  author = {Stubbemann, Maximilian and Hille, Tobias and Hanika, Tom},<br\/>  keywords = {selecting},<br\/>  title = {Selecting Features by their Resilience to the Curse of Dimensionality},<br\/>  year = 2023<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-226d9608a2279971502570f1c18c5fa4\"><p>%0 Journal Article<br\/>%1 stubbemann2023selecting<br\/>%A Stubbemann, Maximilian<br\/>%A Hille, Tobias<br\/>%A Hanika, Tom<br\/>%D 2023<br\/>%T Selecting Features by their Resilience to the Curse of Dimensionality<br\/><\/p><\/div><\/div><\/li><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/article.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Stubbemann, M., Hanika, T., Schneider, F.M.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">Intrinsic Dimension for Large-Scale Geometric Learning<\/span>.<\/span> Transactions on Machine Learning Research. (2023).<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_export bibsonomycsl_abstract\"><a rel=\"abs-292ea436563609314995751c9edb3c43\"  href=\"#\">Abstract<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/openreview.net\/forum?id=85BfDdYMBY\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-292ea436563609314995751c9edb3c43\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-292ea436563609314995751c9edb3c43\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/292ea436563609314995751c9edb3c43\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_abstract\" style=\"display:none;\" id=\"abs-292ea436563609314995751c9edb3c43\">The concept of dimension is essential to grasp the complexity of data. A naive approach to determine the dimension of a dataset is based on the number of attributes. More sophisticated methods derive a notion of intrinsic dimension (ID) that employs more complex feature functions, e.g., distances between data points. Yet, many of these approaches are based on empirical observations, cannot cope with the geometric character of contemporary datasets, and do lack an axiomatic foundation. A different approach was proposed by V. Pestov, who links the intrinsic dimension axiomatically to the mathematical concentration of measure phenomenon. First methods to compute this and related notions for ID were computationally intractable for large-scale real-world datasets. In the present work, we derive a computationally feasible method for determining said axiomatic ID functions. Moreover, we demonstrate how the geometric properties of complex data are accounted for in our modeling. In particular, we propose a principle way to incorporate neighborhood information, as in graph data, into the ID. This allows for new insights into common graph learning procedures, which we illustrate by experiments on the Open Graph Benchmark.<\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-292ea436563609314995751c9edb3c43\"><p>@article{stubbemann2022intrinsic,<br\/>  abstract = {The concept of dimension is essential to grasp the complexity of data. A naive approach to determine the dimension of a dataset is based on the number of attributes. More sophisticated methods derive a notion of intrinsic dimension (ID) that employs more complex feature functions, e.g., distances between data points. Yet, many of these approaches are based on empirical observations, cannot cope with the geometric character of contemporary datasets, and do lack an axiomatic foundation. A different approach was proposed by V. Pestov, who links the intrinsic dimension axiomatically to the mathematical concentration of measure phenomenon. First methods to compute this and related notions for ID were computationally intractable for large-scale real-world datasets. In the present work, we derive a computationally feasible method for determining said axiomatic ID functions. Moreover, we demonstrate how the geometric properties of complex data are accounted for in our modeling. In particular, we propose a principle way to incorporate neighborhood information, as in graph data, into the ID. This allows for new insights into common graph learning procedures, which we illustrate by experiments on the Open Graph Benchmark.},<br\/>  author = {Stubbemann, Maximilian and Hanika, Tom and Schneider, Friedrich Martin},<br\/>  journal = {Transactions on Machine Learning Research},<br\/>  keywords = {itegpub},<br\/>  title = {Intrinsic Dimension for Large-Scale Geometric Learning},<br\/>  year = 2023<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-292ea436563609314995751c9edb3c43\"><p>%0 Journal Article<br\/>%1 stubbemann2022intrinsic<br\/>%A Stubbemann, Maximilian<br\/>%A Hanika, Tom<br\/>%A Schneider, Friedrich Martin<br\/>%D 2023<br\/>%J Transactions on Machine Learning Research<br\/>%T Intrinsic Dimension for Large-Scale Geometric Learning<br\/>%U https:\/\/openreview.net\/forum?id=85BfDdYMBY<br\/>%X The concept of dimension is essential to grasp the complexity of data. A naive approach to determine the dimension of a dataset is based on the number of attributes. More sophisticated methods derive a notion of intrinsic dimension (ID) that employs more complex feature functions, e.g., distances between data points. Yet, many of these approaches are based on empirical observations, cannot cope with the geometric character of contemporary datasets, and do lack an axiomatic foundation. A different approach was proposed by V. Pestov, who links the intrinsic dimension axiomatically to the mathematical concentration of measure phenomenon. First methods to compute this and related notions for ID were computationally intractable for large-scale real-world datasets. In the present work, we derive a computationally feasible method for determining said axiomatic ID functions. Moreover, we demonstrate how the geometric properties of complex data are accounted for in our modeling. In particular, we propose a principle way to incorporate neighborhood information, as in graph data, into the ID. This allows for new insights into common graph learning procedures, which we illustrate by experiments on the Open Graph Benchmark.<br\/><\/p><\/div><\/div><\/li><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/inproceedings.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Hirth, J., Horn, V., Stumme, G., Hanika, T.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">Automatic Textual Explanations of Concept Lattices<\/span>.<\/span> In: Ojeda{-}Aciego, M., Sauerwald, K., and J\u00e4schke, R. (eds.) Graph-Based Representation and Reasoning - 28th International Conference on Conceptual Structures, {ICCS} 2023, Berlin, Germany, September 11-13, 2023, Proceedings. pp. 138\u2013152 (2023). https:\/\/doi.org\/doi.org\/10.1007\/978-3-031-40960-8_12.<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_export bibsonomycsl_abstract\"><a rel=\"abs-3ed37734b0dc428a7cd8ff803cd4e924\"  href=\"#\">Abstract<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"http:\/\/arxiv.org\/abs\/2304.08093\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-3ed37734b0dc428a7cd8ff803cd4e924\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-3ed37734b0dc428a7cd8ff803cd4e924\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"doi.org\/10.1007\/978-3-031-40960-8_12\" target=\"_blank\">DOI<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/3ed37734b0dc428a7cd8ff803cd4e924\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_abstract\" style=\"display:none;\" id=\"abs-3ed37734b0dc428a7cd8ff803cd4e924\">Lattices and their order diagrams are an essential tool for communicating knowledge and insights about data. This is in particular true when applying Formal Concept Analysis. Such representations, however, are difficult to comprehend by untrained users and in general in cases where lattices are large. We tackle this problem by automatically generating textual explanations for lattices using standard scales. Our method is based on the general notion of ordinal motifs in lattices for the special case of standard scales. We show the computational complexity of identifying a small number of standard scales that cover most of the lattice structure. For these, we provide textual explanation templates, which can be applied to any occurrence of a scale in any data domain. These templates are derived using principles from human-computer interaction and allow for a comprehensive textual explanation of lattices. We demonstrate our approach on the spices planner data set, which is a medium sized formal context comprised of fifty-six meals (objects) and thirty-seven spices (attributes). The resulting 531 formal concepts can be covered by means of about 100 standard scales.<\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-3ed37734b0dc428a7cd8ff803cd4e924\"><p>@inproceedings{hirth2023automatic,<br\/>  abstract = {Lattices and their order diagrams are an essential tool for communicating knowledge and insights about data. This is in particular true when applying Formal Concept Analysis. Such representations, however, are difficult to comprehend by untrained users and in general in cases where lattices are large. We tackle this problem by automatically generating textual explanations for lattices using standard scales. Our method is based on the general notion of ordinal motifs in lattices for the special case of standard scales. We show the computational complexity of identifying a small number of standard scales that cover most of the lattice structure. For these, we provide textual explanation templates, which can be applied to any occurrence of a scale in any data domain. These templates are derived using principles from human-computer interaction and allow for a comprehensive textual explanation of lattices. We demonstrate our approach on the spices planner data set, which is a medium sized formal context comprised of fifty-six meals (objects) and thirty-seven spices (attributes). The resulting 531 formal concepts can be covered by means of about 100 standard scales.},<br\/>  author = {Hirth, Johannes and Horn, Viktoria and Stumme, Gerd and Hanika, Tom},<br\/>  booktitle = {Graph-Based Representation and Reasoning - 28th International Conference on Conceptual Structures, {ICCS} 2023, Berlin, Germany, September 11-13, 2023, Proceedings},<br\/>  editor = {Ojeda{-}Aciego, Manuel and Sauerwald, Kai and J\u00e4schke, Robert},<br\/>  keywords = {itegpub},<br\/>  pages = {138--152},<br\/>  title = {Automatic Textual Explanations of Concept Lattices},<br\/>  volume = 14133,<br\/>  year = 2023<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-3ed37734b0dc428a7cd8ff803cd4e924\"><p>%0 Conference Paper<br\/>%1 hirth2023automatic<br\/>%A Hirth, Johannes<br\/>%A Horn, Viktoria<br\/>%A Stumme, Gerd<br\/>%A Hanika, Tom<br\/>%B Graph-Based Representation and Reasoning - 28th International Conference on Conceptual Structures, {ICCS} 2023, Berlin, Germany, September 11-13, 2023, Proceedings<br\/>%D 2023<br\/>%E Ojeda{-}Aciego, Manuel<br\/>%E Sauerwald, Kai<br\/>%E J\u00e4schke, Robert<br\/>%P 138--152<br\/>%R doi.org\/10.1007\/978-3-031-40960-8_12<br\/>%T Automatic Textual Explanations of Concept Lattices<br\/>%U http:\/\/arxiv.org\/abs\/2304.08093<br\/>%V 14133<br\/>%X Lattices and their order diagrams are an essential tool for communicating knowledge and insights about data. This is in particular true when applying Formal Concept Analysis. Such representations, however, are difficult to comprehend by untrained users and in general in cases where lattices are large. We tackle this problem by automatically generating textual explanations for lattices using standard scales. Our method is based on the general notion of ordinal motifs in lattices for the special case of standard scales. We show the computational complexity of identifying a small number of standard scales that cover most of the lattice structure. For these, we provide textual explanation templates, which can be applied to any occurrence of a scale in any data domain. These templates are derived using principles from human-computer interaction and allow for a comprehensive textual explanation of lattices. We demonstrate our approach on the spices planner data set, which is a medium sized formal context comprised of fifty-six meals (objects) and thirty-seven spices (attributes). The resulting 531 formal concepts can be covered by means of about 100 standard scales.<br\/><\/p><\/div><\/div><\/li><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/misc.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Hirth, J., Horn, V., Stumme, G., Hanika, T.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">Ordinal Motifs in Lattices<\/span><\/span>, http:\/\/arxiv.org\/abs\/2304.04827, (2023). https:\/\/doi.org\/10.48550\/arXiv.2304.04827.<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_export bibsonomycsl_abstract\"><a rel=\"abs-b1434de2be43b97abd1c908a0ebaccdd\"  href=\"#\">Abstract<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"http:\/\/arxiv.org\/abs\/2304.04827\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-b1434de2be43b97abd1c908a0ebaccdd\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-b1434de2be43b97abd1c908a0ebaccdd\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/dx.doi.org\/10.48550\/arXiv.2304.04827\" target=\"_blank\">DOI<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/b1434de2be43b97abd1c908a0ebaccdd\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_abstract\" style=\"display:none;\" id=\"abs-b1434de2be43b97abd1c908a0ebaccdd\">Lattices are a commonly used structure for the representation and analysis of relational and ontological knowledge. In particular, the analysis of these requires a decomposition of a large and high-dimensional lattice into a set of understandably large parts. With the present work we propose \/ordinal motifs\/ as analytical units of meaning. We study these ordinal substructures (or standard scales) through (full) scale-measures of formal contexts from the field of formal concept analysis. We show that the underlying decision problems are NP-complete and provide results on how one can incrementally identify ordinal motifs to save computational effort. Accompanying our theoretical results, we demonstrate how ordinal motifs can be leveraged to retrieve basic meaning from a medium sized ordinal data set.<\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-b1434de2be43b97abd1c908a0ebaccdd\"><p>@misc{hirth2023ordinal,<br\/>  abstract = {Lattices are a commonly used structure for the representation and analysis of relational and ontological knowledge. In particular, the analysis of these requires a decomposition of a large and high-dimensional lattice into a set of understandably large parts. With the present work we propose \/ordinal motifs\/ as analytical units of meaning. We study these ordinal substructures (or standard scales) through (full) scale-measures of formal contexts from the field of formal concept analysis. We show that the underlying decision problems are NP-complete and provide results on how one can incrementally identify ordinal motifs to save computational effort. Accompanying our theoretical results, we demonstrate how ordinal motifs can be leveraged to retrieve basic meaning from a medium sized ordinal data set.},<br\/>  author = {Hirth, Johannes and Horn, Viktoria and Stumme, Gerd and Hanika, Tom},<br\/>  keywords = {ordinal},<br\/>  title = {Ordinal Motifs in Lattices},<br\/>  year = 2023<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-b1434de2be43b97abd1c908a0ebaccdd\"><p>%0 Generic<br\/>%1 hirth2023ordinal<br\/>%A Hirth, Johannes<br\/>%A Horn, Viktoria<br\/>%A Stumme, Gerd<br\/>%A Hanika, Tom<br\/>%D 2023<br\/>%R 10.48550\/arXiv.2304.04827<br\/>%T Ordinal Motifs in Lattices<br\/>%U http:\/\/arxiv.org\/abs\/2304.04827<br\/>%X Lattices are a commonly used structure for the representation and analysis of relational and ontological knowledge. In particular, the analysis of these requires a decomposition of a large and high-dimensional lattice into a set of understandably large parts. With the present work we propose \/ordinal motifs\/ as analytical units of meaning. We study these ordinal substructures (or standard scales) through (full) scale-measures of formal contexts from the field of formal concept analysis. We show that the underlying decision problems are NP-complete and provide results on how one can incrementally identify ordinal motifs to save computational effort. Accompanying our theoretical results, we demonstrate how ordinal motifs can be leveraged to retrieve basic meaning from a medium sized ordinal data set.<br\/><\/p><\/div><\/div><\/li><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border\"><img decoding=\"async\" onmouseover=\"javascript:showtrail('https:\/\/www.kde.cs.uni-kassel.de\/en\/hanika\/publications?action=preview&userName=tomhanika&intraHash=3688d07e1cd8318ef9665336665825b5&fileName=2206.07980.pdf&size=LARGE')\" onmouseout=\"javascript:hidetrail()\" class=\"bibsonomycsl_preview\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/en\/hanika\/publications?action=preview&userName=tomhanika&intraHash=3688d07e1cd8318ef9665336665825b5&fileName=2206.07980.pdf&size=SMALL&doc%5B\u0000GuzzleHttp\\Psr7\\Stream\u0000stream%5D=Resource id #68&doc%5B\u0000GuzzleHttp\\Psr7\\Stream\u0000seekable%5D=1&doc%5B\u0000GuzzleHttp\\Psr7\\Stream\u0000readable%5D=1&doc%5B\u0000GuzzleHttp\\Psr7\\Stream\u0000writable%5D=1&doc%5B\u0000GuzzleHttp\\Psr7\\Stream\u0000uri%5D=php:\/\/temp&\" \/><\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Sch\u00e4fermeier, B., Hirth, J., Hanika, T.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">Research Topic Flows in Co-Authorship Networks<\/span>.<\/span> Scientometrics. 128, 5051\u20135078 (2023). https:\/\/doi.org\/10.1007\/s11192-022-04529-w.<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_export bibsonomycsl_abstract\"><a rel=\"abs-3688d07e1cd8318ef9665336665825b5\"  href=\"#\">Abstract<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-3688d07e1cd8318ef9665336665825b5\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-3688d07e1cd8318ef9665336665825b5\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/dx.doi.org\/10.1007\/s11192-022-04529-w\" target=\"_blank\">DOI<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/3688d07e1cd8318ef9665336665825b5\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><span class=\"bibsonomycsl_download\"><a href=\"https:\/\/www.kde.cs.uni-kassel.de\/en\/hanika\/publications?action=download&userName=tomhanika&intraHash=3688d07e1cd8318ef9665336665825b5&fileName=2206.07980.pdf\" target=\"_blank\">Download<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_abstract\" style=\"display:none;\" id=\"abs-3688d07e1cd8318ef9665336665825b5\">In scientometrics, scientific collaboration is often analyzed by means of co-authorships. An aspect which is often overlooked and more difficult to quantify is the flow of expertise between authors from different research topics, which is an important part of scientific progress. With the Topic Flow Network (TFN) we propose a graph structure for the analysis of research topic flows between scientific authors and their respective research fields. Based on a multi-graph and a topic model, our proposed network structure accounts for intratopic as well as intertopic flows. Our method requires for the construction of a TFN solely a corpus of publications (i.e., author and abstract information). From this, research topics are discovered automatically through non-negative matrix factorization. The thereof derived TFN allows for the application of social network analysis techniques, such as common metrics and community detection. Most importantly, it allows for the analysis of intertopic flows on a large, macroscopic scale, i.e., between research topic, as well as on a microscopic scale, i.e., between certain sets of authors. We demonstrate the utility of TFNs by applying our method to two comprehensive corpora of altogether 20 Mio. publications spanning more than 60 years of research in the fields computer science and mathematics. Our results give evidence that TFNs are suitable, e.g., for the analysis of topical communities, the discovery of important authors in different fields, and, most notably, the analysis of intertopic flows, i.e., the transfer of topical expertise. Besides that, our method opens new directions for future research, such as the investigation of influence relationships between research fields.<\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-3688d07e1cd8318ef9665336665825b5\"><p>@article{schafermeier2022research,<br\/>  abstract = {In scientometrics, scientific collaboration is often analyzed by means of co-authorships. An aspect which is often overlooked and more difficult to quantify is the flow of expertise between authors from different research topics, which is an important part of scientific progress. With the Topic Flow Network (TFN) we propose a graph structure for the analysis of research topic flows between scientific authors and their respective research fields. Based on a multi-graph and a topic model, our proposed network structure accounts for intratopic as well as intertopic flows. Our method requires for the construction of a TFN solely a corpus of publications (i.e., author and abstract information). From this, research topics are discovered automatically through non-negative matrix factorization. The thereof derived TFN allows for the application of social network analysis techniques, such as common metrics and community detection. Most importantly, it allows for the analysis of intertopic flows on a large, macroscopic scale, i.e., between research topic, as well as on a microscopic scale, i.e., between certain sets of authors. We demonstrate the utility of TFNs by applying our method to two comprehensive corpora of altogether 20 Mio. publications spanning more than 60 years of research in the fields computer science and mathematics. Our results give evidence that TFNs are suitable, e.g., for the analysis of topical communities, the discovery of important authors in different fields, and, most notably, the analysis of intertopic flows, i.e., the transfer of topical expertise. Besides that, our method opens new directions for future research, such as the investigation of influence relationships between research fields.},<br\/>  author = {Sch\u00e4fermeier, Bastian and Hirth, Johannes and Hanika, Tom},<br\/>  journal = {Scientometrics},<br\/>  keywords = {co-authorships},<br\/>  month = {09},<br\/>  number = 9,<br\/>  pages = {5051--5078},<br\/>  title = {Research Topic Flows in Co-Authorship Networks},<br\/>  volume = 128,<br\/>  year = 2023<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-3688d07e1cd8318ef9665336665825b5\"><p>%0 Journal Article<br\/>%1 schafermeier2022research<br\/>%A Sch\u00e4fermeier, Bastian<br\/>%A Hirth, Johannes<br\/>%A Hanika, Tom<br\/>%D 2023<br\/>%J Scientometrics<br\/>%N 9<br\/>%P 5051--5078<br\/>%R 10.1007\/s11192-022-04529-w<br\/>%T Research Topic Flows in Co-Authorship Networks<br\/>%V 128<br\/>%X In scientometrics, scientific collaboration is often analyzed by means of co-authorships. An aspect which is often overlooked and more difficult to quantify is the flow of expertise between authors from different research topics, which is an important part of scientific progress. With the Topic Flow Network (TFN) we propose a graph structure for the analysis of research topic flows between scientific authors and their respective research fields. Based on a multi-graph and a topic model, our proposed network structure accounts for intratopic as well as intertopic flows. Our method requires for the construction of a TFN solely a corpus of publications (i.e., author and abstract information). From this, research topics are discovered automatically through non-negative matrix factorization. The thereof derived TFN allows for the application of social network analysis techniques, such as common metrics and community detection. Most importantly, it allows for the analysis of intertopic flows on a large, macroscopic scale, i.e., between research topic, as well as on a microscopic scale, i.e., between certain sets of authors. We demonstrate the utility of TFNs by applying our method to two comprehensive corpora of altogether 20 Mio. publications spanning more than 60 years of research in the fields computer science and mathematics. Our results give evidence that TFNs are suitable, e.g., for the analysis of topical communities, the discovery of important authors in different fields, and, most notably, the analysis of intertopic flows, i.e., the transfer of topical expertise. Besides that, our method opens new directions for future research, such as the investigation of influence relationships between research fields.<br\/><\/p><\/div><\/div><\/li>\n<\/ul>\n<a class=\"bibsonomycsl_publications-headline-anchor \" name=\"jmp_2022\"><\/a><h3 class=\"bibsonomycsl_publications-headline\" style=\"font-size: 1.1em; font-weight: bold;\">2022<\/h3>\n<ul class=\"bibsonomycsl_publications\"><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/article.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Hanika, T., Hirth, J.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">Knowledge cores in large formal contexts<\/span>.<\/span> Annals of Mathematics and Artificial Intelligence. 90, 537\u2013567 (2022). https:\/\/doi.org\/10.1007\/s10472-022-09790-6.<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_export bibsonomycsl_abstract\"><a rel=\"abs-0a621f4c0749385cfebf7b44efdf3a03\"  href=\"#\">Abstract<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/doi.org\/10.1007\/s10472-022-09790-6\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-0a621f4c0749385cfebf7b44efdf3a03\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-0a621f4c0749385cfebf7b44efdf3a03\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/dx.doi.org\/10.1007\/s10472-022-09790-6\" target=\"_blank\">DOI<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/0a621f4c0749385cfebf7b44efdf3a03\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_abstract\" style=\"display:none;\" id=\"abs-0a621f4c0749385cfebf7b44efdf3a03\">Knowledge computation tasks, such as computing a base of valid implications, are often infeasible for large data sets. This is in particular true when deriving canonical bases in formal concept analysis (FCA). Therefore, it is necessary to find techniques that on the one hand reduce the data set size, but on the other hand preserve enough structure to extract useful knowledge. Many successful methods are based on random processes to reduce the size of the investigated data set. This, however, makes them hardly interpretable with respect to the discovered knowledge. Other approaches restrict themselves to highly supported subsets and omit rare and (maybe) interesting patterns. An essentially different approach is used in network science, called k-cores. These cores are able to reflect rare patterns, as long as they are well connected within the data set. In this work, we study k-cores in the realm of FCA by exploiting the natural correspondence of bi-partite graphs and formal contexts. This structurally motivated approach leads to a comprehensible extraction of knowledge cores from large formal contexts.<\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-0a621f4c0749385cfebf7b44efdf3a03\"><p>@article{Hanika2022,<br\/>  abstract = {Knowledge computation tasks, such as computing a base of valid implications, are often infeasible for large data sets. This is in particular true when deriving canonical bases in formal concept analysis (FCA). Therefore, it is necessary to find techniques that on the one hand reduce the data set size, but on the other hand preserve enough structure to extract useful knowledge. Many successful methods are based on random processes to reduce the size of the investigated data set. This, however, makes them hardly interpretable with respect to the discovered knowledge. Other approaches restrict themselves to highly supported subsets and omit rare and (maybe) interesting patterns. An essentially different approach is used in network science, called k-cores. These cores are able to reflect rare patterns, as long as they are well connected within the data set. In this work, we study k-cores in the realm of FCA by exploiting the natural correspondence of bi-partite graphs and formal contexts. This structurally motivated approach leads to a comprehensible extraction of knowledge cores from large formal contexts.},<br\/>  author = {Hanika, Tom and Hirth, Johannes},<br\/>  journal = {Annals of Mathematics and Artificial Intelligence},<br\/>  keywords = {itegpub},<br\/>  month = {04},<br\/>  number = 6,<br\/>  pages = {537--567},<br\/>  title = {Knowledge cores in large formal contexts},<br\/>  volume = 90,<br\/>  year = 2022<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-0a621f4c0749385cfebf7b44efdf3a03\"><p>%0 Journal Article<br\/>%1 Hanika2022<br\/>%A Hanika, Tom<br\/>%A Hirth, Johannes<br\/>%D 2022<br\/>%J Annals of Mathematics and Artificial Intelligence<br\/>%N 6<br\/>%P 537--567<br\/>%R 10.1007\/s10472-022-09790-6<br\/>%T Knowledge cores in large formal contexts<br\/>%U https:\/\/doi.org\/10.1007\/s10472-022-09790-6<br\/>%V 90<br\/>%X Knowledge computation tasks, such as computing a base of valid implications, are often infeasible for large data sets. This is in particular true when deriving canonical bases in formal concept analysis (FCA). Therefore, it is necessary to find techniques that on the one hand reduce the data set size, but on the other hand preserve enough structure to extract useful knowledge. Many successful methods are based on random processes to reduce the size of the investigated data set. This, however, makes them hardly interpretable with respect to the discovered knowledge. Other approaches restrict themselves to highly supported subsets and omit rare and (maybe) interesting patterns. An essentially different approach is used in network science, called k-cores. These cores are able to reflect rare patterns, as long as they are well connected within the data set. In this work, we study k-cores in the realm of FCA by exploiting the natural correspondence of bi-partite graphs and formal contexts. This structurally motivated approach leads to a comprehensible extraction of knowledge cores from large formal contexts.<br\/><\/p><\/div><\/div><\/li><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/incollection.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">D{{\u00fc}}rrschnabel, D., Hanika, T., Stubbemann, M.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">{FCA2VEC:} Embedding Techniques for Formal Concept Analysis<\/span>.<\/span> In: Missaoui, R., Kwuida, L., and Abdessalem, T. (eds.) Complex Data Analytics with Formal Concept Analysis. pp. 47\u201374. Springer International Publishing (2022). https:\/\/doi.org\/10.1007\/978-3-030-93278-7_3.<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/doi.org\/10.1007\/978-3-030-93278-7_3\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-e127e1457fc3ea1df732f8cc594915a5\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-e127e1457fc3ea1df732f8cc594915a5\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/dx.doi.org\/10.1007\/978-3-030-93278-7_3\" target=\"_blank\">DOI<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/e127e1457fc3ea1df732f8cc594915a5\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-e127e1457fc3ea1df732f8cc594915a5\"><p>@incollection{DBLP:books\/sp\/missaoui2022\/DurrschnabelHS22,<br\/>  author = {D{{\u00fc}}rrschnabel, Dominik and Hanika, Tom and Stubbemann, Maximilian},<br\/>  booktitle = {Complex Data Analytics with Formal Concept Analysis},<br\/>  editor = {Missaoui, Rokia and Kwuida, L{{\u00e9}}onard and Abdessalem, Talel},<br\/>  keywords = {itegpub},<br\/>  pages = {47--74},<br\/>  publisher = {Springer International Publishing},<br\/>  title = {{FCA2VEC:} Embedding Techniques for Formal Concept Analysis},<br\/>  year = 2022<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-e127e1457fc3ea1df732f8cc594915a5\"><p>%0 Book Section<br\/>%1 DBLP:books\/sp\/missaoui2022\/DurrschnabelHS22<br\/>%A D{{\u00fc}}rrschnabel, Dominik<br\/>%A Hanika, Tom<br\/>%A Stubbemann, Maximilian<br\/>%B Complex Data Analytics with Formal Concept Analysis<br\/>%D 2022<br\/>%E Missaoui, Rokia<br\/>%E Kwuida, L{{\u00e9}}onard<br\/>%E Abdessalem, Talel<br\/>%I Springer International Publishing<br\/>%P 47--74<br\/>%R 10.1007\/978-3-030-93278-7_3<br\/>%T {FCA2VEC:} Embedding Techniques for Formal Concept Analysis<br\/>%U https:\/\/doi.org\/10.1007\/978-3-030-93278-7_3<br\/><\/p><\/div><\/div><\/li><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border\"><img decoding=\"async\" onmouseover=\"javascript:showtrail('https:\/\/www.kde.cs.uni-kassel.de\/en\/hanika\/publications?action=preview&userName=tomhanika&intraHash=156354a19a4fadcf64beaf678ff4c44e&fileName=2204.11859.pdf&size=LARGE')\" onmouseout=\"javascript:hidetrail()\" class=\"bibsonomycsl_preview\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/en\/hanika\/publications?action=preview&userName=tomhanika&intraHash=156354a19a4fadcf64beaf678ff4c44e&fileName=2204.11859.pdf&size=SMALL&doc%5B\u0000GuzzleHttp\\Psr7\\Stream\u0000stream%5D=Resource id #75&doc%5B\u0000GuzzleHttp\\Psr7\\Stream\u0000seekable%5D=1&doc%5B\u0000GuzzleHttp\\Psr7\\Stream\u0000readable%5D=1&doc%5B\u0000GuzzleHttp\\Psr7\\Stream\u0000writable%5D=1&doc%5B\u0000GuzzleHttp\\Psr7\\Stream\u0000uri%5D=php:\/\/temp&\" \/><\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Sch\u00e4fermeier, B., Stumme, G., Hanika, T.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">Mapping Research Trajectories<\/span><\/span>, https:\/\/arxiv.org\/abs\/2204.11859, (2022). https:\/\/doi.org\/10.48550\/ARXIV.2204.11859.<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/arxiv.org\/abs\/2204.11859\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-156354a19a4fadcf64beaf678ff4c44e\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-156354a19a4fadcf64beaf678ff4c44e\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/dx.doi.org\/10.48550\/ARXIV.2204.11859\" target=\"_blank\">DOI<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/156354a19a4fadcf64beaf678ff4c44e\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><span class=\"bibsonomycsl_download\"><a href=\"https:\/\/www.kde.cs.uni-kassel.de\/en\/hanika\/publications?action=download&userName=tomhanika&intraHash=156354a19a4fadcf64beaf678ff4c44e&fileName=2204.11859.pdf\" target=\"_blank\">Download<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-156354a19a4fadcf64beaf678ff4c44e\"><p>@misc{https:\/\/doi.org\/10.48550\/arxiv.2204.11859,<br\/>  author = {Sch\u00e4fermeier, Bastian and Stumme, Gerd and Hanika, Tom},<br\/>  keywords = {research},<br\/>  publisher = {arXiv},<br\/>  title = {Mapping Research Trajectories},<br\/>  year = 2022<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-156354a19a4fadcf64beaf678ff4c44e\"><p>%0 Generic<br\/>%1 https:\/\/doi.org\/10.48550\/arxiv.2204.11859<br\/>%A Sch\u00e4fermeier, Bastian<br\/>%A Stumme, Gerd<br\/>%A Hanika, Tom<br\/>%D 2022<br\/>%I arXiv<br\/>%R 10.48550\/ARXIV.2204.11859<br\/>%T Mapping Research Trajectories<br\/>%U https:\/\/arxiv.org\/abs\/2204.11859<br\/><\/p><\/div><\/div><\/li><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border\"><img decoding=\"async\" onmouseover=\"javascript:showtrail('https:\/\/www.kde.cs.uni-kassel.de\/en\/hanika\/publications?action=preview&userName=tomhanika&intraHash=d40a5033ba022c8f88208c8ec83eb171&fileName=2209.13517.pdf&size=LARGE')\" onmouseout=\"javascript:hidetrail()\" class=\"bibsonomycsl_preview\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/en\/hanika\/publications?action=preview&userName=tomhanika&intraHash=d40a5033ba022c8f88208c8ec83eb171&fileName=2209.13517.pdf&size=SMALL&doc%5B\u0000GuzzleHttp\\Psr7\\Stream\u0000stream%5D=Resource id #80&doc%5B\u0000GuzzleHttp\\Psr7\\Stream\u0000seekable%5D=1&doc%5B\u0000GuzzleHttp\\Psr7\\Stream\u0000readable%5D=1&doc%5B\u0000GuzzleHttp\\Psr7\\Stream\u0000writable%5D=1&doc%5B\u0000GuzzleHttp\\Psr7\\Stream\u0000uri%5D=php:\/\/temp&\" \/><\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Hirth, J., Hanika, T.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">Formal Conceptual Views in Neural Networks<\/span><\/span>, http:\/\/arxiv.org\/abs\/2209.13517, (2022).<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_export bibsonomycsl_abstract\"><a rel=\"abs-d40a5033ba022c8f88208c8ec83eb171\"  href=\"#\">Abstract<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"http:\/\/arxiv.org\/abs\/2209.13517\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-d40a5033ba022c8f88208c8ec83eb171\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-d40a5033ba022c8f88208c8ec83eb171\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/d40a5033ba022c8f88208c8ec83eb171\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><span class=\"bibsonomycsl_download\"><a href=\"https:\/\/www.kde.cs.uni-kassel.de\/en\/hanika\/publications?action=download&userName=tomhanika&intraHash=d40a5033ba022c8f88208c8ec83eb171&fileName=2209.13517.pdf\" target=\"_blank\">Download<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_abstract\" style=\"display:none;\" id=\"abs-d40a5033ba022c8f88208c8ec83eb171\">Explaining neural network models is a challenging task that remains unsolved in its entirety to this day. This is especially true for high dimensional and complex data. With the present work, we introduce two notions for conceptual views of a neural network, specifically a many-valued and a symbolic view. Both provide novel analysis methods to enable a human AI analyst to grasp deeper insights into the knowledge that is captured by the neurons of a network. We test the conceptual expressivity of our novel views through different experiments on the ImageNet and Fruit-360 data sets. Furthermore, we show to which extent the views allow to quantify the conceptual similarity of different learning architectures. Finally, we demonstrate how conceptual views can be applied for abductive learning of human comprehensible rules from neurons. In summary, with our work, we contribute to the most relevant task of globally explaining neural networks models.<\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-d40a5033ba022c8f88208c8ec83eb171\"><p>@misc{hirth2022formal,<br\/>  abstract = {Explaining neural network models is a challenging task that remains unsolved in its entirety to this day. This is especially true for high dimensional and complex data. With the present work, we introduce two notions for conceptual views of a neural network, specifically a many-valued and a symbolic view. Both provide novel analysis methods to enable a human AI analyst to grasp deeper insights into the knowledge that is captured by the neurons of a network. We test the conceptual expressivity of our novel views through different experiments on the ImageNet and Fruit-360 data sets. Furthermore, we show to which extent the views allow to quantify the conceptual similarity of different learning architectures. Finally, we demonstrate how conceptual views can be applied for abductive learning of human comprehensible rules from neurons. In summary, with our work, we contribute to the most relevant task of globally explaining neural networks models.},<br\/>  author = {Hirth, Johannes and Hanika, Tom},<br\/>  keywords = {NN},<br\/>  note = {cite arxiv:2209.13517Comment: 17 pages, 8 figures, 9 tables},<br\/>  title = {Formal Conceptual Views in Neural Networks},<br\/>  year = 2022<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-d40a5033ba022c8f88208c8ec83eb171\"><p>%0 Generic<br\/>%1 hirth2022formal<br\/>%A Hirth, Johannes<br\/>%A Hanika, Tom<br\/>%D 2022<br\/>%T Formal Conceptual Views in Neural Networks<br\/>%U http:\/\/arxiv.org\/abs\/2209.13517<br\/>%X Explaining neural network models is a challenging task that remains unsolved in its entirety to this day. This is especially true for high dimensional and complex data. With the present work, we introduce two notions for conceptual views of a neural network, specifically a many-valued and a symbolic view. Both provide novel analysis methods to enable a human AI analyst to grasp deeper insights into the knowledge that is captured by the neurons of a network. We test the conceptual expressivity of our novel views through different experiments on the ImageNet and Fruit-360 data sets. Furthermore, we show to which extent the views allow to quantify the conceptual similarity of different learning architectures. Finally, we demonstrate how conceptual views can be applied for abductive learning of human comprehensible rules from neurons. In summary, with our work, we contribute to the most relevant task of globally explaining neural networks models.<br\/><\/p><\/div><\/div><\/li><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/article.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Hanika, T., Schneider, F.M., Stumme, G.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">{Intrinsic dimension of geometric data sets}<\/span>.<\/span> Tohoku Mathematical Journal. 74, 23\u201352 (2022). https:\/\/doi.org\/10.2748\/tmj.20201015a.<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_export bibsonomycsl_abstract\"><a rel=\"abs-34cd317c997745ba26b40684b702987a\"  href=\"#\">Abstract<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/doi.org\/10.2748\/tmj.20201015a\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-34cd317c997745ba26b40684b702987a\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-34cd317c997745ba26b40684b702987a\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/dx.doi.org\/10.2748\/tmj.20201015a\" target=\"_blank\">DOI<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/34cd317c997745ba26b40684b702987a\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_abstract\" style=\"display:none;\" id=\"abs-34cd317c997745ba26b40684b702987a\">The curse of dimensionality is a phenomenon frequently observed in machine learning (ML) and knowledge discovery (KD). There is a large body of literature investigating its origin and impact, using methods from mathematics as well as from computer science. Among the mathematical insights into data dimensionality, there is an intimate link between the dimension curse and the phenomenon of measure concentration, which makes the former accessible to methods of geometric analysis. The present work provides a comprehensive study of the intrinsic geometry of a data set, based on Gromov's metric measure geometry and Pestov's axiomatic approach to intrinsic dimension. In detail, we define a concept of geometric data set and introduce a metric as well as a partial order on the set of isomorphism classes of such data sets. Based on these objects, we propose and investigate an axiomatic approach to the intrinsic dimension of geometric data sets and establish a concrete dimension function with the desired properties. Our model for data sets and their intrinsic dimension is computationally feasible and, moreover, adaptable to specific ML\/KD-algorithms, as illustrated by various experiments.<\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-34cd317c997745ba26b40684b702987a\"><p>@article{10.2748\/tmj.20201015a,<br\/>  abstract = {The curse of dimensionality is a phenomenon frequently observed in machine learning (ML) and knowledge discovery (KD). There is a large body of literature investigating its origin and impact, using methods from mathematics as well as from computer science. Among the mathematical insights into data dimensionality, there is an intimate link between the dimension curse and the phenomenon of measure concentration, which makes the former accessible to methods of geometric analysis. The present work provides a comprehensive study of the intrinsic geometry of a data set, based on Gromov's metric measure geometry and Pestov's axiomatic approach to intrinsic dimension. In detail, we define a concept of geometric data set and introduce a metric as well as a partial order on the set of isomorphism classes of such data sets. Based on these objects, we propose and investigate an axiomatic approach to the intrinsic dimension of geometric data sets and establish a concrete dimension function with the desired properties. Our model for data sets and their intrinsic dimension is computationally feasible and, moreover, adaptable to specific ML\/KD-algorithms, as illustrated by various experiments.},<br\/>  author = {Hanika, Tom and Schneider, Friedrich Martin and Stumme, Gerd},<br\/>  journal = {Tohoku Mathematical Journal},<br\/>  keywords = {itegpub},<br\/>  number = 1,<br\/>  pages = {23 -- 52},<br\/>  publisher = {Tohoku University, Mathematical Institute},<br\/>  title = {{Intrinsic dimension of geometric data sets}},<br\/>  volume = 74,<br\/>  year = 2022<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-34cd317c997745ba26b40684b702987a\"><p>%0 Journal Article<br\/>%1 10.2748\/tmj.20201015a<br\/>%A Hanika, Tom<br\/>%A Schneider, Friedrich Martin<br\/>%A Stumme, Gerd<br\/>%D 2022<br\/>%I Tohoku University, Mathematical Institute<br\/>%J Tohoku Mathematical Journal<br\/>%N 1<br\/>%P 23 -- 52<br\/>%R 10.2748\/tmj.20201015a<br\/>%T {Intrinsic dimension of geometric data sets}<br\/>%U https:\/\/doi.org\/10.2748\/tmj.20201015a<br\/>%V 74<br\/>%X The curse of dimensionality is a phenomenon frequently observed in machine learning (ML) and knowledge discovery (KD). There is a large body of literature investigating its origin and impact, using methods from mathematics as well as from computer science. Among the mathematical insights into data dimensionality, there is an intimate link between the dimension curse and the phenomenon of measure concentration, which makes the former accessible to methods of geometric analysis. The present work provides a comprehensive study of the intrinsic geometry of a data set, based on Gromov's metric measure geometry and Pestov's axiomatic approach to intrinsic dimension. In detail, we define a concept of geometric data set and introduce a metric as well as a partial order on the set of isomorphism classes of such data sets. Based on these objects, we propose and investigate an axiomatic approach to the intrinsic dimension of geometric data sets and establish a concrete dimension function with the desired properties. Our model for data sets and their intrinsic dimension is computationally feasible and, moreover, adaptable to specific ML\/KD-algorithms, as illustrated by various experiments.<br\/><\/p><\/div><\/div><\/li><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/article.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Hanika, T., Hirth, J.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">On the lattice of conceptual measurements<\/span>.<\/span> Information Sciences. 613, 453\u2013468 (2022). https:\/\/doi.org\/https:\/\/doi.org\/10.1016\/j.ins.2022.09.005.<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_export bibsonomycsl_abstract\"><a rel=\"abs-752bc4553487e6472b22faf56e744cad\"  href=\"#\">Abstract<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0020025522010489\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-752bc4553487e6472b22faf56e744cad\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-752bc4553487e6472b22faf56e744cad\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/doi.org\/10.1016\/j.ins.2022.09.005\" target=\"_blank\">DOI<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/752bc4553487e6472b22faf56e744cad\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_abstract\" style=\"display:none;\" id=\"abs-752bc4553487e6472b22faf56e744cad\">We present a novel approach for data set scaling based on scale-measures from formal concept analysis, i.e., continuous maps between closure systems, for which we derive a canonical representation. Moreover, we prove that scale-measures can be lattice ordered using the canonical representation. This enables exploring the set of scale-measures by the use of meet and join operations. Furthermore we show that the lattice of scale-measures is isomorphic to the lattice of sub-closure systems that arises from the original data. Finally, we provide another representation of scale-measures using propositional logic in terms of data set features. Our theoretical findings are discussed by means of examples.<\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-752bc4553487e6472b22faf56e744cad\"><p>@article{HANIKA2022453,<br\/>  abstract = {We present a novel approach for data set scaling based on scale-measures from formal concept analysis, i.e., continuous maps between closure systems, for which we derive a canonical representation. Moreover, we prove that scale-measures can be lattice ordered using the canonical representation. This enables exploring the set of scale-measures by the use of meet and join operations. Furthermore we show that the lattice of scale-measures is isomorphic to the lattice of sub-closure systems that arises from the original data. Finally, we provide another representation of scale-measures using propositional logic in terms of data set features. Our theoretical findings are discussed by means of examples.},<br\/>  author = {Hanika, Tom and Hirth, Johannes},<br\/>  journal = {Information Sciences},<br\/>  keywords = {kdepub},<br\/>  pages = {453-468},<br\/>  title = {On the lattice of conceptual measurements},<br\/>  volume = 613,<br\/>  year = 2022<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-752bc4553487e6472b22faf56e744cad\"><p>%0 Journal Article<br\/>%1 HANIKA2022453<br\/>%A Hanika, Tom<br\/>%A Hirth, Johannes<br\/>%D 2022<br\/>%J Information Sciences<br\/>%P 453-468<br\/>%R https:\/\/doi.org\/10.1016\/j.ins.2022.09.005<br\/>%T On the lattice of conceptual measurements<br\/>%U https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0020025522010489<br\/>%V 613<br\/>%X We present a novel approach for data set scaling based on scale-measures from formal concept analysis, i.e., continuous maps between closure systems, for which we derive a canonical representation. Moreover, we prove that scale-measures can be lattice ordered using the canonical representation. This enables exploring the set of scale-measures by the use of meet and join operations. Furthermore we show that the lattice of scale-measures is isomorphic to the lattice of sub-closure systems that arises from the original data. Finally, we provide another representation of scale-measures using propositional logic in terms of data set features. Our theoretical findings are discussed by means of examples.<br\/><\/p><\/div><\/div><\/li>\n<\/ul>\n<a class=\"bibsonomycsl_publications-headline-anchor \" name=\"jmp_2021\"><\/a><h3 class=\"bibsonomycsl_publications-headline\" style=\"font-size: 1.1em; font-weight: bold;\">2021<\/h3>\n<ul class=\"bibsonomycsl_publications\"><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border\"><img decoding=\"async\" onmouseover=\"javascript:showtrail('https:\/\/www.kde.cs.uni-kassel.de\/en\/hanika\/publications?action=preview&userName=tomhanika&intraHash=319304ff625ee98746f680b13cf3c6d7&fileName=paper.pdf&size=LARGE')\" onmouseout=\"javascript:hidetrail()\" class=\"bibsonomycsl_preview\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/en\/hanika\/publications?action=preview&userName=tomhanika&intraHash=319304ff625ee98746f680b13cf3c6d7&fileName=paper.pdf&size=SMALL&doc%5B\u0000GuzzleHttp\\Psr7\\Stream\u0000stream%5D=Resource id #87&doc%5B\u0000GuzzleHttp\\Psr7\\Stream\u0000seekable%5D=1&doc%5B\u0000GuzzleHttp\\Psr7\\Stream\u0000readable%5D=1&doc%5B\u0000GuzzleHttp\\Psr7\\Stream\u0000writable%5D=1&doc%5B\u0000GuzzleHttp\\Psr7\\Stream\u0000uri%5D=php:\/\/temp&\" \/><\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Schaefermeier, B., Stumme, G., Hanika, T.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">Topological Indoor Mapping through WiFi Signals<\/span>.<\/span> (2021).<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_export bibsonomycsl_abstract\"><a rel=\"abs-319304ff625ee98746f680b13cf3c6d7\"  href=\"#\">Abstract<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"http:\/\/arxiv.org\/abs\/2106.09789\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-319304ff625ee98746f680b13cf3c6d7\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-319304ff625ee98746f680b13cf3c6d7\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/319304ff625ee98746f680b13cf3c6d7\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><span class=\"bibsonomycsl_download\"><a href=\"https:\/\/www.kde.cs.uni-kassel.de\/en\/hanika\/publications?action=download&userName=tomhanika&intraHash=319304ff625ee98746f680b13cf3c6d7&fileName=paper.pdf\" target=\"_blank\">Download<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_abstract\" style=\"display:none;\" id=\"abs-319304ff625ee98746f680b13cf3c6d7\">The ubiquitous presence of WiFi access points and mobile devices capable of measuring WiFi signal strengths allow for real-world applications in indoor localization and mapping. In particular, no additional infrastructure is required. Previous approaches in this field were, however, often hindered by problems such as effortful map-building processes, changing environments and hardware differences. We tackle these problems focussing on topological maps. These represent discrete locations, such as rooms, and their relations, e.g., distances and transition frequencies. In our unsupervised method, we employ WiFi signal strength distributions, dimension reduction and clustering. It can be used in settings where users carry mobile devices and follow their normal routine. We aim for applications in short-lived indoor events such as conferences.<\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-319304ff625ee98746f680b13cf3c6d7\"><p>@article{schaefermeier2021topological,<br\/>  abstract = {The ubiquitous presence of WiFi access points and mobile devices capable of measuring WiFi signal strengths allow for real-world applications in indoor localization and mapping. In particular, no additional infrastructure is required. Previous approaches in this field were, however, often hindered by problems such as effortful map-building processes, changing environments and hardware differences. We tackle these problems focussing on topological maps. These represent discrete locations, such as rooms, and their relations, e.g., distances and transition frequencies. In our unsupervised method, we employ WiFi signal strength distributions, dimension reduction and clustering. It can be used in settings where users carry mobile devices and follow their normal routine. We aim for applications in short-lived indoor events such as conferences.},<br\/>  author = {Schaefermeier, Bastian and Stumme, Gerd and Hanika, Tom},<br\/>  keywords = {topological},<br\/>  note = {cite arxiv:2106.09789Comment: 18 pages},<br\/>  title = {Topological Indoor Mapping through WiFi Signals},<br\/>  year = 2021<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-319304ff625ee98746f680b13cf3c6d7\"><p>%0 Journal Article<br\/>%1 schaefermeier2021topological<br\/>%A Schaefermeier, Bastian<br\/>%A Stumme, Gerd<br\/>%A Hanika, Tom<br\/>%D 2021<br\/>%T Topological Indoor Mapping through WiFi Signals<br\/>%U http:\/\/arxiv.org\/abs\/2106.09789<br\/>%X The ubiquitous presence of WiFi access points and mobile devices capable of measuring WiFi signal strengths allow for real-world applications in indoor localization and mapping. In particular, no additional infrastructure is required. Previous approaches in this field were, however, often hindered by problems such as effortful map-building processes, changing environments and hardware differences. We tackle these problems focussing on topological maps. These represent discrete locations, such as rooms, and their relations, e.g., distances and transition frequencies. In our unsupervised method, we employ WiFi signal strength distributions, dimension reduction and clustering. It can be used in settings where users carry mobile devices and follow their normal routine. We aim for applications in short-lived indoor events such as conferences.<br\/><\/p><\/div><\/div><\/li><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/inproceedings.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Hanika, T., Hirth, J.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">Quantifying the Conceptual Error in Dimensionality Reduction<\/span>.<\/span> In: Braun, T., Gehrke, M., Hanika, T., and Hernandez, N. (eds.) Graph-Based Representation and Reasoning - 26th International Conference on Conceptual Structures, {ICCS} 2021, Virtual Event, September 20-22, 2021, Proceedings. pp. 105\u2013118. Springer (2021). https:\/\/doi.org\/10.1007\/978-3-030-86982-3_8.<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/doi.org\/10.1007\/978-3-030-86982-3_8\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-bccd47524af1f4528212c2b971ed9c54\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-bccd47524af1f4528212c2b971ed9c54\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/dx.doi.org\/10.1007\/978-3-030-86982-3_8\" target=\"_blank\">DOI<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/bccd47524af1f4528212c2b971ed9c54\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-bccd47524af1f4528212c2b971ed9c54\"><p>@inproceedings{DBLP:conf\/iccs\/HanikaH21,<br\/>  author = {Hanika, Tom and Hirth, Johannes},<br\/>  booktitle = {Graph-Based Representation and Reasoning - 26th International Conference on Conceptual Structures, {ICCS} 2021, Virtual Event, September 20-22, 2021, Proceedings},<br\/>  editor = {Braun, Tanya and Gehrke, Marcel and Hanika, Tom and Hernandez, Nathalie},<br\/>  keywords = {itegpub},<br\/>  pages = {105--118},<br\/>  publisher = {Springer},<br\/>  series = {Lecture Notes in Computer Science},<br\/>  title = {Quantifying the Conceptual Error in Dimensionality Reduction},<br\/>  volume = 12879,<br\/>  year = 2021<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-bccd47524af1f4528212c2b971ed9c54\"><p>%0 Conference Paper<br\/>%1 DBLP:conf\/iccs\/HanikaH21<br\/>%A Hanika, Tom<br\/>%A Hirth, Johannes<br\/>%B Graph-Based Representation and Reasoning - 26th International Conference on Conceptual Structures, {ICCS} 2021, Virtual Event, September 20-22, 2021, Proceedings<br\/>%D 2021<br\/>%E Braun, Tanya<br\/>%E Gehrke, Marcel<br\/>%E Hanika, Tom<br\/>%E Hernandez, Nathalie<br\/>%I Springer<br\/>%P 105--118<br\/>%R 10.1007\/978-3-030-86982-3_8<br\/>%T Quantifying the Conceptual Error in Dimensionality Reduction<br\/>%U https:\/\/doi.org\/10.1007\/978-3-030-86982-3_8<br\/>%V 12879<br\/><\/p><\/div><\/div><\/li><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/proceedings.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Braud, A., Buzmakov, A., Hanika, T., Ber, F.L. eds.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">Formal Concept Analysis - 16th International Conference, {ICFCA} 2021, Strasbourg, France, June 29 - July 2, 2021, Proceedings<\/span>.<\/span> Springer (2021). https:\/\/doi.org\/10.1007\/978-3-030-77867-5.<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/doi.org\/10.1007\/978-3-030-77867-5\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-2800bb018f9e09ad5efdc51dadcb7e0c\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-2800bb018f9e09ad5efdc51dadcb7e0c\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/dx.doi.org\/10.1007\/978-3-030-77867-5\" target=\"_blank\">DOI<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/2800bb018f9e09ad5efdc51dadcb7e0c\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-2800bb018f9e09ad5efdc51dadcb7e0c\"><p>@proceedings{DBLP:conf\/icfca\/2021,<br\/>  editor = {Braud, Agn{{\u00e8}}s and Buzmakov, Aleksey and Hanika, Tom and Ber, Florence Le},<br\/>  keywords = {itegpub},<br\/>  publisher = {Springer},<br\/>  series = {Lecture Notes in Computer Science},<br\/>  title = {Formal Concept Analysis - 16th International Conference, {ICFCA} 2021, Strasbourg, France, June 29 - July 2, 2021, Proceedings},<br\/>  volume = 12733,<br\/>  year = 2021<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-2800bb018f9e09ad5efdc51dadcb7e0c\"><p>%0 Conference Proceedings<br\/>%1 DBLP:conf\/icfca\/2021<br\/>%B Lecture Notes in Computer Science<br\/>%D 2021<br\/>%E Braud, Agn{{\u00e8}}s<br\/>%E Buzmakov, Aleksey<br\/>%E Hanika, Tom<br\/>%E Ber, Florence Le<br\/>%I Springer<br\/>%R 10.1007\/978-3-030-77867-5<br\/>%T Formal Concept Analysis - 16th International Conference, {ICFCA} 2021, Strasbourg, France, June 29 - July 2, 2021, Proceedings<br\/>%U https:\/\/doi.org\/10.1007\/978-3-030-77867-5<br\/>%V 12733<br\/>%@ 978-3-030-77866-8<br\/><\/p><\/div><\/div><\/li><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border\"><img decoding=\"async\" onmouseover=\"javascript:showtrail('https:\/\/www.kde.cs.uni-kassel.de\/en\/hanika\/publications?action=preview&userName=tomhanika&intraHash=9472cccf5ce51f6faaead874d76fc216&fileName=Schaefermeier2021_Article_TopicSpaceTrajectories+%281%29.pdf&size=LARGE')\" onmouseout=\"javascript:hidetrail()\" class=\"bibsonomycsl_preview\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/en\/hanika\/publications?action=preview&userName=tomhanika&intraHash=9472cccf5ce51f6faaead874d76fc216&fileName=Schaefermeier2021_Article_TopicSpaceTrajectories+%281%29.pdf&size=SMALL&doc%5B\u0000GuzzleHttp\\Psr7\\Stream\u0000stream%5D=Resource id #94&doc%5B\u0000GuzzleHttp\\Psr7\\Stream\u0000seekable%5D=1&doc%5B\u0000GuzzleHttp\\Psr7\\Stream\u0000readable%5D=1&doc%5B\u0000GuzzleHttp\\Psr7\\Stream\u0000writable%5D=1&doc%5B\u0000GuzzleHttp\\Psr7\\Stream\u0000uri%5D=php:\/\/temp&\" \/><\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Schaefermeier, B., Stumme, G., Hanika, T.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">Topic space trajectories<\/span>.<\/span> Scientometrics. 126, 5759\u20135795 (2021). https:\/\/doi.org\/10.1007\/s11192-021-03931-0.<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_export bibsonomycsl_abstract\"><a rel=\"abs-9472cccf5ce51f6faaead874d76fc216\"  href=\"#\">Abstract<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/doi.org\/10.1007\/s11192-021-03931-0\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-9472cccf5ce51f6faaead874d76fc216\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-9472cccf5ce51f6faaead874d76fc216\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/dx.doi.org\/10.1007\/s11192-021-03931-0\" target=\"_blank\">DOI<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/9472cccf5ce51f6faaead874d76fc216\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><span class=\"bibsonomycsl_download\"><a href=\"https:\/\/www.kde.cs.uni-kassel.de\/en\/hanika\/publications?action=download&userName=tomhanika&intraHash=9472cccf5ce51f6faaead874d76fc216&fileName=Schaefermeier2021_Article_TopicSpaceTrajectories+%281%29.pdf\" target=\"_blank\">Download<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_abstract\" style=\"display:none;\" id=\"abs-9472cccf5ce51f6faaead874d76fc216\">The annual number of publications at scientific venues, for example, conferences and journals, is growing quickly. Hence, even for researchers it becomes harder and harder to keep track of research topics and their progress. In this task, researchers can be supported by automated publication analysis. Yet, many such methods result in uninterpretable, purely numerical representations. As an attempt to support human analysts, we present topic space trajectories, a structure that allows for the comprehensible tracking of research topics. We demonstrate how these trajectories can be interpreted based on eight different analysis approaches. To obtain comprehensible results, we employ non-negative matrix factorization as well as suitable visualization techniques. We show the applicability of our approach on a publication corpus spanning 50\u00a0years of machine learning research from 32 publication venues. In addition to a thorough introduction of our method, our focus is on an extensive analysis of the results we achieved. Our novel analysis method may be employed for paper classification, for the prediction of future research topics, and for the recommendation of fitting conferences and journals for submitting unpublished work. An advantage in these applications over previous methods lies in the good interpretability of the results obtained through our methods.<\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-9472cccf5ce51f6faaead874d76fc216\"><p>@article{Schaefermeier2021,<br\/>  abstract = {The annual number of publications at scientific venues, for example, conferences and journals, is growing quickly. Hence, even for researchers it becomes harder and harder to keep track of research topics and their progress. In this task, researchers can be supported by automated publication analysis. Yet, many such methods result in uninterpretable, purely numerical representations. As an attempt to support human analysts, we present topic space trajectories, a structure that allows for the comprehensible tracking of research topics. We demonstrate how these trajectories can be interpreted based on eight different analysis approaches. To obtain comprehensible results, we employ non-negative matrix factorization as well as suitable visualization techniques. We show the applicability of our approach on a publication corpus spanning 50\u00a0years of machine learning research from 32 publication venues. In addition to a thorough introduction of our method, our focus is on an extensive analysis of the results we achieved. Our novel analysis method may be employed for paper classification, for the prediction of future research topics, and for the recommendation of fitting conferences and journals for submitting unpublished work. An advantage in these applications over previous methods lies in the good interpretability of the results obtained through our methods.},<br\/>  author = {Schaefermeier, Bastian and Stumme, Gerd and Hanika, Tom},<br\/>  journal = {Scientometrics},<br\/>  keywords = {itegpub},<br\/>  month = {05},<br\/>  number = 7,<br\/>  pages = {5759\u20135795},<br\/>  title = {Topic space trajectories},<br\/>  volume = 126,<br\/>  year = 2021<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-9472cccf5ce51f6faaead874d76fc216\"><p>%0 Journal Article<br\/>%1 Schaefermeier2021<br\/>%A Schaefermeier, Bastian<br\/>%A Stumme, Gerd<br\/>%A Hanika, Tom<br\/>%D 2021<br\/>%J Scientometrics<br\/>%N 7<br\/>%P 5759\u20135795<br\/>%R 10.1007\/s11192-021-03931-0<br\/>%T Topic space trajectories<br\/>%U https:\/\/doi.org\/10.1007\/s11192-021-03931-0<br\/>%V 126<br\/>%X The annual number of publications at scientific venues, for example, conferences and journals, is growing quickly. Hence, even for researchers it becomes harder and harder to keep track of research topics and their progress. In this task, researchers can be supported by automated publication analysis. Yet, many such methods result in uninterpretable, purely numerical representations. As an attempt to support human analysts, we present topic space trajectories, a structure that allows for the comprehensible tracking of research topics. We demonstrate how these trajectories can be interpreted based on eight different analysis approaches. To obtain comprehensible results, we employ non-negative matrix factorization as well as suitable visualization techniques. We show the applicability of our approach on a publication corpus spanning 50\u00a0years of machine learning research from 32 publication venues. In addition to a thorough introduction of our method, our focus is on an extensive analysis of the results we achieved. Our novel analysis method may be employed for paper classification, for the prediction of future research topics, and for the recommendation of fitting conferences and journals for submitting unpublished work. An advantage in these applications over previous methods lies in the good interpretability of the results obtained through our methods.<br\/><\/p><\/div><\/div><\/li><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/proceedings.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Braun, T., Gehrke, M., Hanika, T., Hernandez, N. eds.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">Graph-Based Representation and Reasoning - 26th International Conference on Conceptual Structures, {ICCS} 2021, Virtual Event, September 20-22, 2021, Proceedings<\/span>.<\/span> Springer (2021). https:\/\/doi.org\/10.1007\/978-3-030-86982-3.<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/doi.org\/10.1007\/978-3-030-86982-3\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-31038bd7ccf83ec063c645daffcbe899\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-31038bd7ccf83ec063c645daffcbe899\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/dx.doi.org\/10.1007\/978-3-030-86982-3\" target=\"_blank\">DOI<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/31038bd7ccf83ec063c645daffcbe899\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-31038bd7ccf83ec063c645daffcbe899\"><p>@proceedings{DBLP:conf\/iccs\/2021,<br\/>  editor = {Braun, Tanya and Gehrke, Marcel and Hanika, Tom and Hernandez, Nathalie},<br\/>  keywords = {itegpub},<br\/>  publisher = {Springer},<br\/>  series = {Lecture Notes in Computer Science},<br\/>  title = {Graph-Based Representation and Reasoning - 26th International Conference on Conceptual Structures, {ICCS} 2021, Virtual Event, September 20-22, 2021, Proceedings},<br\/>  volume = 12879,<br\/>  year = 2021<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-31038bd7ccf83ec063c645daffcbe899\"><p>%0 Conference Proceedings<br\/>%1 DBLP:conf\/iccs\/2021<br\/>%B Lecture Notes in Computer Science<br\/>%D 2021<br\/>%E Braun, Tanya<br\/>%E Gehrke, Marcel<br\/>%E Hanika, Tom<br\/>%E Hernandez, Nathalie<br\/>%I Springer<br\/>%R 10.1007\/978-3-030-86982-3<br\/>%T Graph-Based Representation and Reasoning - 26th International Conference on Conceptual Structures, {ICCS} 2021, Virtual Event, September 20-22, 2021, Proceedings<br\/>%U https:\/\/doi.org\/10.1007\/978-3-030-86982-3<br\/>%V 12879<br\/>%@ 978-3-030-86981-6<br\/><\/p><\/div><\/div><\/li><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/inproceedings.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Hanika, T., Hirth, J.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">Exploring Scale-Measures of Data Sets<\/span>.<\/span> In: Braud, A., Buzmakov, A., Hanika, T., and Ber, F.L. (eds.) Formal Concept Analysis - 16th International Conference, {ICFCA} 2021, Strasbourg, France, June 29 - July 2, 2021, Proceedings. pp. 261\u2013269. Springer (2021). https:\/\/doi.org\/10.1007\/978-3-030-77867-5_17.<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/doi.org\/10.1007\/978-3-030-77867-5_17\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-6ddf8be80b973b6693c80c1b7b3bfd91\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-6ddf8be80b973b6693c80c1b7b3bfd91\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/dx.doi.org\/10.1007\/978-3-030-77867-5_17\" target=\"_blank\">DOI<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/6ddf8be80b973b6693c80c1b7b3bfd91\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-6ddf8be80b973b6693c80c1b7b3bfd91\"><p>@inproceedings{DBLP:conf\/icfca\/HanikaH21,<br\/>  author = {Hanika, Tom and Hirth, Johannes},<br\/>  booktitle = {Formal Concept Analysis - 16th International Conference, {ICFCA} 2021, Strasbourg, France, June 29 - July 2, 2021, Proceedings},<br\/>  editor = {Braud, Agn{{\u00e8}}s and Buzmakov, Aleksey and Hanika, Tom and Ber, Florence Le},<br\/>  keywords = {itegpub},<br\/>  pages = {261--269},<br\/>  publisher = {Springer},<br\/>  series = {Lecture Notes in Computer Science},<br\/>  title = {Exploring Scale-Measures of Data Sets},<br\/>  volume = 12733,<br\/>  year = 2021<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-6ddf8be80b973b6693c80c1b7b3bfd91\"><p>%0 Conference Paper<br\/>%1 DBLP:conf\/icfca\/HanikaH21<br\/>%A Hanika, Tom<br\/>%A Hirth, Johannes<br\/>%B Formal Concept Analysis - 16th International Conference, {ICFCA} 2021, Strasbourg, France, June 29 - July 2, 2021, Proceedings<br\/>%D 2021<br\/>%E Braud, Agn{{\u00e8}}s<br\/>%E Buzmakov, Aleksey<br\/>%E Hanika, Tom<br\/>%E Ber, Florence Le<br\/>%I Springer<br\/>%P 261--269<br\/>%R 10.1007\/978-3-030-77867-5_17<br\/>%T Exploring Scale-Measures of Data Sets<br\/>%U https:\/\/doi.org\/10.1007\/978-3-030-77867-5_17<br\/>%V 12733<br\/><\/p><\/div><\/div><\/li><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/article.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Koopmann, T., Stubbemann, M., Kapa, M., Paris, M., Buenstorf, G., Hanika, T., Hotho, A., J\u00e4schke, R., Stumme, G.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">Proximity dimensions and the emergence of collaboration: a HypTrails study on German AI research<\/span>.<\/span> Scientometrics. (2021). https:\/\/doi.org\/10.1007\/s11192-021-03922-1.<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_export bibsonomycsl_abstract\"><a rel=\"abs-403544c0381c5a42e340c6f288bee105\"  href=\"#\">Abstract<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/link.springer.com\/article\/10.1007\/s11192-021-03922-1\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-403544c0381c5a42e340c6f288bee105\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-403544c0381c5a42e340c6f288bee105\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/dx.doi.org\/10.1007\/s11192-021-03922-1\" target=\"_blank\">DOI<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/403544c0381c5a42e340c6f288bee105\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_abstract\" style=\"display:none;\" id=\"abs-403544c0381c5a42e340c6f288bee105\">Creation and exchange of knowledge depends on collaboration. Recent work has suggested that the emergence of collaboration frequently relies on geographic proximity. However, being co-located tends to be associated with other dimensions of proximity, such as social ties or a shared organizational environment. To account for such factors, multiple dimensions of proximity have been proposed, including cognitive, institutional, organizational, social and geographical proximity. Since they strongly interrelate, disentangling these dimensions and their respective impact on collaboration is challenging. To address this issue, we propose various methods for measuring different dimensions of proximity. We then present an approach to compare and rank them with respect to the extent to which they indicate co-publications and co-inventions. We adapt the HypTrails approach, which was originally developed to explain human navigation, to co-author and co-inventor graphs. We evaluate this approach on a subset of the German research community, specifically academic authors and inventors active in research on artificial intelligence (AI). We find that social proximity and cognitive proximity are more important for the emergence of collaboration than geographic proximity.<\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-403544c0381c5a42e340c6f288bee105\"><p>@article{koopmann2021proximity,<br\/>  abstract = {Creation and exchange of knowledge depends on collaboration. Recent work has suggested that the emergence of collaboration frequently relies on geographic proximity. However, being co-located tends to be associated with other dimensions of proximity, such as social ties or a shared organizational environment. To account for such factors, multiple dimensions of proximity have been proposed, including cognitive, institutional, organizational, social and geographical proximity. Since they strongly interrelate, disentangling these dimensions and their respective impact on collaboration is challenging. To address this issue, we propose various methods for measuring different dimensions of proximity. We then present an approach to compare and rank them with respect to the extent to which they indicate co-publications and co-inventions. We adapt the HypTrails approach, which was originally developed to explain human navigation, to co-author and co-inventor graphs. We evaluate this approach on a subset of the German research community, specifically academic authors and inventors active in research on artificial intelligence (AI). We find that social proximity and cognitive proximity are more important for the emergence of collaboration than geographic proximity.},<br\/>  author = {Koopmann, Tobias and Stubbemann, Maximilian and Kapa, Matthias and Paris, Michael and Buenstorf, Guido and Hanika, Tom and Hotho, Andreas and J\u00e4schke, Robert and Stumme, Gerd},<br\/>  journal = {Scientometrics},<br\/>  keywords = {itegpub},<br\/>  month = {03},<br\/>  title = {Proximity dimensions and the emergence of collaboration: a HypTrails study on German AI research},<br\/>  year = 2021<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-403544c0381c5a42e340c6f288bee105\"><p>%0 Journal Article<br\/>%1 koopmann2021proximity<br\/>%A Koopmann, Tobias<br\/>%A Stubbemann, Maximilian<br\/>%A Kapa, Matthias<br\/>%A Paris, Michael<br\/>%A Buenstorf, Guido<br\/>%A Hanika, Tom<br\/>%A Hotho, Andreas<br\/>%A J\u00e4schke, Robert<br\/>%A Stumme, Gerd<br\/>%D 2021<br\/>%J Scientometrics<br\/>%R 10.1007\/s11192-021-03922-1<br\/>%T Proximity dimensions and the emergence of collaboration: a HypTrails study on German AI research<br\/>%U https:\/\/link.springer.com\/article\/10.1007\/s11192-021-03922-1<br\/>%X Creation and exchange of knowledge depends on collaboration. Recent work has suggested that the emergence of collaboration frequently relies on geographic proximity. However, being co-located tends to be associated with other dimensions of proximity, such as social ties or a shared organizational environment. To account for such factors, multiple dimensions of proximity have been proposed, including cognitive, institutional, organizational, social and geographical proximity. Since they strongly interrelate, disentangling these dimensions and their respective impact on collaboration is challenging. To address this issue, we propose various methods for measuring different dimensions of proximity. We then present an approach to compare and rank them with respect to the extent to which they indicate co-publications and co-inventions. We adapt the HypTrails approach, which was originally developed to explain human navigation, to co-author and co-inventor graphs. We evaluate this approach on a subset of the German research community, specifically academic authors and inventors active in research on artificial intelligence (AI). We find that social proximity and cognitive proximity are more important for the emergence of collaboration than geographic proximity.<br\/><\/p><\/div><\/div><\/li>\n<\/ul>\n<a class=\"bibsonomycsl_publications-headline-anchor \" name=\"jmp_2020\"><\/a><h3 class=\"bibsonomycsl_publications-headline\" style=\"font-size: 1.1em; font-weight: bold;\">2020<\/h3>\n<ul class=\"bibsonomycsl_publications\"><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border\"><img decoding=\"async\" onmouseover=\"javascript:showtrail('https:\/\/www.kde.cs.uni-kassel.de\/en\/hanika\/publications?action=preview&userName=tomhanika&intraHash=5af4dfd0c1a213f76e3b4a265c680846&fileName=information-11-00135.pdf&size=LARGE')\" onmouseout=\"javascript:hidetrail()\" class=\"bibsonomycsl_preview\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/en\/hanika\/publications?action=preview&userName=tomhanika&intraHash=5af4dfd0c1a213f76e3b4a265c680846&fileName=information-11-00135.pdf&size=SMALL&doc%5B\u0000GuzzleHttp\\Psr7\\Stream\u0000stream%5D=Resource id #102&doc%5B\u0000GuzzleHttp\\Psr7\\Stream\u0000seekable%5D=1&doc%5B\u0000GuzzleHttp\\Psr7\\Stream\u0000readable%5D=1&doc%5B\u0000GuzzleHttp\\Psr7\\Stream\u0000writable%5D=1&doc%5B\u0000GuzzleHttp\\Psr7\\Stream\u0000uri%5D=php:\/\/temp&\" \/><\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Felde, M., Hanika, T., Stumme, G.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">Null Models for Formal Contexts<\/span>.<\/span> Information. 11, 135 (2020).<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.mdpi.com\/2078-2489\/11\/3\/135\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-5af4dfd0c1a213f76e3b4a265c680846\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-5af4dfd0c1a213f76e3b4a265c680846\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/5af4dfd0c1a213f76e3b4a265c680846\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><span class=\"bibsonomycsl_download\"><a href=\"https:\/\/www.kde.cs.uni-kassel.de\/en\/hanika\/publications?action=download&userName=tomhanika&intraHash=5af4dfd0c1a213f76e3b4a265c680846&fileName=information-11-00135.pdf\" target=\"_blank\">Download<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-5af4dfd0c1a213f76e3b4a265c680846\"><p>@article{felde2020null,<br\/>  author = {Felde, Maximilian and Hanika, Tom and Stumme, Gerd},<br\/>  journal = {Information},<br\/>  keywords = {itegpub},<br\/>  number = 3,<br\/>  pages = 135,<br\/>  publisher = {Multidisciplinary Digital Publishing Institute},<br\/>  title = {Null Models for Formal Contexts},<br\/>  volume = 11,<br\/>  year = 2020<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-5af4dfd0c1a213f76e3b4a265c680846\"><p>%0 Journal Article<br\/>%1 felde2020null<br\/>%A Felde, Maximilian<br\/>%A Hanika, Tom<br\/>%A Stumme, Gerd<br\/>%D 2020<br\/>%I Multidisciplinary Digital Publishing Institute<br\/>%J Information<br\/>%N 3<br\/>%P 135<br\/>%T Null Models for Formal Contexts<br\/>%U https:\/\/www.mdpi.com\/2078-2489\/11\/3\/135<br\/>%V 11<br\/><\/p><\/div><\/div><\/li><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/inproceedings.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Stubbemann, M., Hanika, T., Stumme, G.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">Orometric Methods in Bounded Metric Data<\/span>.<\/span> In: Berthold, M.R., Feelders, A., and Krempl, G. (eds.) Advances in Intelligent Data Analysis {XVIII} - 18th International Symposium on Intelligent Data Analysis, {IDA} 2020, Konstanz, Germany, April 27-29, 2020, Proceedings. pp. 496\u2013508. Springer (2020). https:\/\/doi.org\/10.1007\/978-3-030-44584-3_39.<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/doi.org\/10.1007\/978-3-030-44584-3\\_39\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-46473c28ad59dcf47f2dbe1427740370\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-46473c28ad59dcf47f2dbe1427740370\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/dx.doi.org\/10.1007\/978-3-030-44584-3_39\" target=\"_blank\">DOI<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/46473c28ad59dcf47f2dbe1427740370\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-46473c28ad59dcf47f2dbe1427740370\"><p>@inproceedings{DBLP:conf\/ida\/StubbemannHS20,<br\/>  author = {Stubbemann, Maximilian and Hanika, Tom and Stumme, Gerd},<br\/>  booktitle = {Advances in Intelligent Data Analysis {XVIII} - 18th International Symposium on Intelligent Data Analysis, {IDA} 2020, Konstanz, Germany, April 27-29, 2020, Proceedings},<br\/>  editor = {Berthold, Michael R. and Feelders, Ad and Krempl, Georg},<br\/>  keywords = {itegpub},<br\/>  pages = {496--508},<br\/>  publisher = {Springer},<br\/>  series = {Lecture Notes in Computer Science},<br\/>  title = {Orometric Methods in Bounded Metric Data},<br\/>  volume = 12080,<br\/>  year = 2020<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-46473c28ad59dcf47f2dbe1427740370\"><p>%0 Conference Paper<br\/>%1 DBLP:conf\/ida\/StubbemannHS20<br\/>%A Stubbemann, Maximilian<br\/>%A Hanika, Tom<br\/>%A Stumme, Gerd<br\/>%B Advances in Intelligent Data Analysis {XVIII} - 18th International Symposium on Intelligent Data Analysis, {IDA} 2020, Konstanz, Germany, April 27-29, 2020, Proceedings<br\/>%D 2020<br\/>%E Berthold, Michael R.<br\/>%E Feelders, Ad<br\/>%E Krempl, Georg<br\/>%I Springer<br\/>%P 496--508<br\/>%R 10.1007\/978-3-030-44584-3_39<br\/>%T Orometric Methods in Bounded Metric Data<br\/>%U https:\/\/doi.org\/10.1007\/978-3-030-44584-3\\_39<br\/>%V 12080<br\/><\/p><\/div><\/div><\/li><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/article.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Borchmann, D., Hanika, T., Obiedkov, S.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">Probably approximately correct learning of Horn envelopes from queries<\/span>.<\/span> Discrete Applied Mathematics. 273, 30\u201342 (2020). https:\/\/doi.org\/https:\/\/doi.org\/10.1016\/j.dam.2019.02.036.<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_export bibsonomycsl_abstract\"><a rel=\"abs-be121e13826f0ad3699d2629f08cc77f\"  href=\"#\">Abstract<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"http:\/\/www.sciencedirect.com\/science\/article\/pii\/S0166218X19301295\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-be121e13826f0ad3699d2629f08cc77f\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-be121e13826f0ad3699d2629f08cc77f\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/doi.org\/10.1016\/j.dam.2019.02.036\" target=\"_blank\">DOI<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/be121e13826f0ad3699d2629f08cc77f\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_abstract\" style=\"display:none;\" id=\"abs-be121e13826f0ad3699d2629f08cc77f\">We propose an algorithm for learning the Horn envelope of an arbitrary domain using an expert, or an oracle, capable of answering certain types of queries about this domain. Attribute exploration from formal concept analysis is a procedure that solves this problem, but the number of queries it may ask is exponential in the size of the resulting Horn formula in the worst case. We recall a well-known polynomial-time algorithm for learning Horn formulas with membership and equivalence queries and modify it to obtain a polynomial-time probably approximately correct algorithm for learning the Horn envelope of an arbitrary domain.<\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-be121e13826f0ad3699d2629f08cc77f\"><p>@article{BORCHMANN202030,<br\/>  abstract = {We propose an algorithm for learning the Horn envelope of an arbitrary domain using an expert, or an oracle, capable of answering certain types of queries about this domain. Attribute exploration from formal concept analysis is a procedure that solves this problem, but the number of queries it may ask is exponential in the size of the resulting Horn formula in the worst case. We recall a well-known polynomial-time algorithm for learning Horn formulas with membership and equivalence queries and modify it to obtain a polynomial-time probably approximately correct algorithm for learning the Horn envelope of an arbitrary domain.},<br\/>  author = {Borchmann, Daniel and Hanika, Tom and Obiedkov, Sergei},<br\/>  journal = {Discrete Applied Mathematics},<br\/>  keywords = {itegpub},<br\/>  note = {Advances in Formal Concept Analysis: Traces of CLA 2016},<br\/>  pages = {30 - 42},<br\/>  title = {Probably approximately correct learning of Horn envelopes from queries},<br\/>  volume = 273,<br\/>  year = 2020<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-be121e13826f0ad3699d2629f08cc77f\"><p>%0 Journal Article<br\/>%1 BORCHMANN202030<br\/>%A Borchmann, Daniel<br\/>%A Hanika, Tom<br\/>%A Obiedkov, Sergei<br\/>%D 2020<br\/>%J Discrete Applied Mathematics<br\/>%P 30 - 42<br\/>%R https:\/\/doi.org\/10.1016\/j.dam.2019.02.036<br\/>%T Probably approximately correct learning of Horn envelopes from queries<br\/>%U http:\/\/www.sciencedirect.com\/science\/article\/pii\/S0166218X19301295<br\/>%V 273<br\/>%X We propose an algorithm for learning the Horn envelope of an arbitrary domain using an expert, or an oracle, capable of answering certain types of queries about this domain. Attribute exploration from formal concept analysis is a procedure that solves this problem, but the number of queries it may ask is exponential in the size of the resulting Horn formula in the worst case. We recall a well-known polynomial-time algorithm for learning Horn formulas with membership and equivalence queries and modify it to obtain a polynomial-time probably approximately correct algorithm for learning the Horn envelope of an arbitrary domain.<br\/><\/p><\/div><\/div><\/li>\n<\/ul>\n<a class=\"bibsonomycsl_publications-headline-anchor \" name=\"jmp_2019\"><\/a><h3 class=\"bibsonomycsl_publications-headline\" style=\"font-size: 1.1em; font-weight: bold;\">2019<\/h3>\n<ul class=\"bibsonomycsl_publications\"><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/inproceedings.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Hanika, T., Marx, M., Stumme, G.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">Discovering Implicational Knowledge in Wikidata.<\/span><\/span> In: Cristea, D., Ber, F.L., and Sertkaya, B. (eds.) ICFCA. pp. 315\u2013323. Springer (2019). https:\/\/doi.org\/10.1007\/978-3-030-21462-3_21.<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_url\"><a href=\"http:\/\/dblp.uni-trier.de\/db\/conf\/icfca\/icfca2019.html#Hanika0S19\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-0af109b0a6a727a7f76833b1284d952f\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-0af109b0a6a727a7f76833b1284d952f\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/dx.doi.org\/10.1007\/978-3-030-21462-3_21\" target=\"_blank\">DOI<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/0af109b0a6a727a7f76833b1284d952f\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-0af109b0a6a727a7f76833b1284d952f\"><p>@inproceedings{conf\/icfca\/Hanika0S19,<br\/>  author = {Hanika, Tom and Marx, Maximilian and Stumme, Gerd},<br\/>  booktitle = {ICFCA},<br\/>  crossref = {conf\/icfca\/2019},<br\/>  editor = {Cristea, Diana and Ber, Florence Le and Sertkaya, Baris},<br\/>  keywords = {itegpub},<br\/>  pages = {315-323},<br\/>  publisher = {Springer},<br\/>  series = {Lecture Notes in Computer Science},<br\/>  title = {Discovering Implicational Knowledge in Wikidata.},<br\/>  volume = 11511,<br\/>  year = 2019<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-0af109b0a6a727a7f76833b1284d952f\"><p>%0 Conference Paper<br\/>%1 conf\/icfca\/Hanika0S19<br\/>%A Hanika, Tom<br\/>%A Marx, Maximilian<br\/>%A Stumme, Gerd<br\/>%B ICFCA<br\/>%D 2019<br\/>%E Cristea, Diana<br\/>%E Ber, Florence Le<br\/>%E Sertkaya, Baris<br\/>%I Springer<br\/>%P 315-323<br\/>%R 10.1007\/978-3-030-21462-3_21<br\/>%T Discovering Implicational Knowledge in Wikidata.<br\/>%U http:\/\/dblp.uni-trier.de\/db\/conf\/icfca\/icfca2019.html#Hanika0S19<br\/>%V 11511<br\/>%@ 978-3-030-21462-3<br\/><\/p><\/div><\/div><\/li><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/inproceedings.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Hanika, T., Hirth, J.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">Conexp-Clj - A Research Tool for FCA.<\/span><\/span> In: Cristea, D., Ber, F.L., Missaoui, R., Kwuida, L., and Sertkaya, B. (eds.) ICFCA (Supplements). pp. 70\u201375. CEUR-WS.org (2019).<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_url\"><a href=\"http:\/\/dblp.uni-trier.de\/db\/conf\/icfca\/icfca2019suppl.html#HanikaH19\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-432006ec0f26e5c6c5e26900faadc7e3\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-432006ec0f26e5c6c5e26900faadc7e3\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/432006ec0f26e5c6c5e26900faadc7e3\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-432006ec0f26e5c6c5e26900faadc7e3\"><p>@inproceedings{conf\/icfca\/HanikaH19,<br\/>  author = {Hanika, Tom and Hirth, Johannes},<br\/>  booktitle = {ICFCA (Supplements)},<br\/>  crossref = {conf\/icfca\/2019suppl},<br\/>  editor = {Cristea, Diana and Ber, Florence Le and Missaoui, Rokia and Kwuida, L\u00e9onard and Sertkaya, Baris},<br\/>  keywords = {itegpub},<br\/>  pages = {70-75},<br\/>  publisher = {CEUR-WS.org},<br\/>  series = {CEUR Workshop Proceedings},<br\/>  title = {Conexp-Clj - A Research Tool for FCA.},<br\/>  volume = 2378,<br\/>  year = 2019<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-432006ec0f26e5c6c5e26900faadc7e3\"><p>%0 Conference Paper<br\/>%1 conf\/icfca\/HanikaH19<br\/>%A Hanika, Tom<br\/>%A Hirth, Johannes<br\/>%B ICFCA (Supplements)<br\/>%D 2019<br\/>%E Cristea, Diana<br\/>%E Ber, Florence Le<br\/>%E Missaoui, Rokia<br\/>%E Kwuida, L\u00e9onard<br\/>%E Sertkaya, Baris<br\/>%I CEUR-WS.org<br\/>%P 70-75<br\/>%T Conexp-Clj - A Research Tool for FCA.<br\/>%U http:\/\/dblp.uni-trier.de\/db\/conf\/icfca\/icfca2019suppl.html#HanikaH19<br\/>%V 2378<br\/><\/p><\/div><\/div><\/li><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/incollection.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Hanika, T., Kibanov, M., Kropf, J., Laser, S.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">Ich denke, es ist wichtig zu verstehen, warum die Netzwerkanalyse jetzt popul{\u00e4}r und besonders interessant f{\u00fc}r die Forschung geworden ist.<\/span><\/span> In: Kropf, J. and Laser, S. (eds.) Digitale Bewertungspraktiken. pp. 165\u2013188. Springer (2019).<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-1676016925aa18edb753d477bc8be2e9\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-1676016925aa18edb753d477bc8be2e9\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/1676016925aa18edb753d477bc8be2e9\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-1676016925aa18edb753d477bc8be2e9\"><p>@incollection{hanika2019denke,<br\/>  author = {Hanika, Tom and Kibanov, Mark and Kropf, Jonathan and Laser, Stefan},<br\/>  booktitle = {Digitale Bewertungspraktiken},<br\/>  editor = {Kropf, Jonathan and Laser, Stefan},<br\/>  keywords = {bewertungspraktiken},<br\/>  pages = {165--188},<br\/>  publisher = {Springer},<br\/>  title = {Ich denke, es ist wichtig zu verstehen, warum die Netzwerkanalyse jetzt popul{\u00e4}r und besonders interessant f{\u00fc}r die Forschung geworden ist.},<br\/>  year = 2019<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-1676016925aa18edb753d477bc8be2e9\"><p>%0 Book Section<br\/>%1 hanika2019denke<br\/>%A Hanika, Tom<br\/>%A Kibanov, Mark<br\/>%A Kropf, Jonathan<br\/>%A Laser, Stefan<br\/>%B Digitale Bewertungspraktiken<br\/>%D 2019<br\/>%E Kropf, Jonathan<br\/>%E Laser, Stefan<br\/>%I Springer<br\/>%P 165--188<br\/>%T Ich denke, es ist wichtig zu verstehen, warum die Netzwerkanalyse jetzt popul{\u00e4}r und besonders interessant f{\u00fc}r die Forschung geworden ist.<br\/><\/p><\/div><\/div><\/li><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/article.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Hanika, T., Herde, M., Kuhn, J., Leimeister, J.M., Lukowicz, P., Oeste-Rei\u00df, S., Schmidt, A., Sick, B., Stumme, G., Tomforde, S., Zweig, K.A.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">Collaborative Interactive Learning - A clarification of terms and a differentiation from other research fields.<\/span><\/span> CoRR. abs\/1905.07264, (2019).<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_url\"><a href=\"http:\/\/dblp.uni-trier.de\/db\/journals\/corr\/corr1905.html#abs-1905-07264\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-490e9c0fd28c8886ae8e296e1530c219\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-490e9c0fd28c8886ae8e296e1530c219\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/490e9c0fd28c8886ae8e296e1530c219\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-490e9c0fd28c8886ae8e296e1530c219\"><p>@article{journals\/corr\/abs-1905-07264,<br\/>  author = {Hanika, Tom and Herde, Marek and Kuhn, Jochen and Leimeister, Jan Marco and Lukowicz, Paul and Oeste-Rei\u00df, Sarah and Schmidt, Albrecht and Sick, Bernhard and Stumme, Gerd and Tomforde, Sven and Zweig, Katharina Anna},<br\/>  journal = {CoRR},<br\/>  keywords = {kde},<br\/>  title = {Collaborative Interactive Learning - A clarification of terms and a differentiation from other research fields.},<br\/>  volume = {abs\/1905.07264},<br\/>  year = 2019<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-490e9c0fd28c8886ae8e296e1530c219\"><p>%0 Journal Article<br\/>%1 journals\/corr\/abs-1905-07264<br\/>%A Hanika, Tom<br\/>%A Herde, Marek<br\/>%A Kuhn, Jochen<br\/>%A Leimeister, Jan Marco<br\/>%A Lukowicz, Paul<br\/>%A Oeste-Rei\u00df, Sarah<br\/>%A Schmidt, Albrecht<br\/>%A Sick, Bernhard<br\/>%A Stumme, Gerd<br\/>%A Tomforde, Sven<br\/>%A Zweig, Katharina Anna<br\/>%D 2019<br\/>%J CoRR<br\/>%T Collaborative Interactive Learning - A clarification of terms and a differentiation from other research fields.<br\/>%U http:\/\/dblp.uni-trier.de\/db\/journals\/corr\/corr1905.html#abs-1905-07264<br\/>%V abs\/1905.07264<br\/><\/p><\/div><\/div><\/li><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/misc.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">D\u00fcrrschnabel, D., Hanika, T., Stumme, G.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">Drawing Order Diagrams Through Two-Dimension Extension<\/span><\/span>, http:\/\/arxiv.org\/abs\/1906.06208, (2019).<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_export bibsonomycsl_abstract\"><a rel=\"abs-a33b056dcfcf90c67f1c183ed4664501\"  href=\"#\">Abstract<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"http:\/\/arxiv.org\/abs\/1906.06208\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-a33b056dcfcf90c67f1c183ed4664501\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-a33b056dcfcf90c67f1c183ed4664501\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/a33b056dcfcf90c67f1c183ed4664501\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_abstract\" style=\"display:none;\" id=\"abs-a33b056dcfcf90c67f1c183ed4664501\">Order diagrams are an important tool to visualize the complex structure of ordered sets. Favorable drawings of order diagrams, i.e., easily readable for humans, are hard to come by, even for small ordered sets. Many attempts were made to transfer classical graph drawing approaches to order diagrams. Although these methods produce satisfying results for some ordered sets, they unfortunately perform poorly in general. In this work we present the novel algorithm DimDraw to draw order diagrams. This algorithm is based on a relation between the dimension of an ordered set and the bipartiteness of a corresponding graph.<\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-a33b056dcfcf90c67f1c183ed4664501\"><p>@misc{durrschnabel2019drawing,<br\/>  abstract = {Order diagrams are an important tool to visualize the complex structure of ordered sets. Favorable drawings of order diagrams, i.e., easily readable for humans, are hard to come by, even for small ordered sets. Many attempts were made to transfer classical graph drawing approaches to order diagrams. Although these methods produce satisfying results for some ordered sets, they unfortunately perform poorly in general. In this work we present the novel algorithm DimDraw to draw order diagrams. This algorithm is based on a relation between the dimension of an ordered set and the bipartiteness of a corresponding graph.},<br\/>  author = {D\u00fcrrschnabel, Dominik and Hanika, Tom and Stumme, Gerd},<br\/>  keywords = {order},<br\/>  note = {cite arxiv:1906.06208Comment: 16 pages, 12 Figures},<br\/>  title = {Drawing Order Diagrams Through Two-Dimension Extension},<br\/>  year = 2019<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-a33b056dcfcf90c67f1c183ed4664501\"><p>%0 Generic<br\/>%1 durrschnabel2019drawing<br\/>%A D\u00fcrrschnabel, Dominik<br\/>%A Hanika, Tom<br\/>%A Stumme, Gerd<br\/>%D 2019<br\/>%T Drawing Order Diagrams Through Two-Dimension Extension<br\/>%U http:\/\/arxiv.org\/abs\/1906.06208<br\/>%X Order diagrams are an important tool to visualize the complex structure of ordered sets. Favorable drawings of order diagrams, i.e., easily readable for humans, are hard to come by, even for small ordered sets. Many attempts were made to transfer classical graph drawing approaches to order diagrams. Although these methods produce satisfying results for some ordered sets, they unfortunately perform poorly in general. In this work we present the novel algorithm DimDraw to draw order diagrams. This algorithm is based on a relation between the dimension of an ordered set and the bipartiteness of a corresponding graph.<br\/><\/p><\/div><\/div><\/li><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/inproceedings.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Felde, M., Hanika, T.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">Formal Context Generation Using Dirichlet Distributions.<\/span><\/span> In: Endres, D., Alam, M., and Sotropa, D. (eds.) ICCS. pp. 57\u201371. Springer (2019). https:\/\/doi.org\/10.1007\/978-3-030-23182-8_5.<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_url\"><a href=\"http:\/\/dblp.uni-trier.de\/db\/conf\/iccs\/iccs2019.html#FeldeH19\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-3150e7472057f04f6e9e2da1954671ab\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-3150e7472057f04f6e9e2da1954671ab\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/dx.doi.org\/10.1007\/978-3-030-23182-8_5\" target=\"_blank\">DOI<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/3150e7472057f04f6e9e2da1954671ab\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-3150e7472057f04f6e9e2da1954671ab\"><p>@inproceedings{conf\/iccs\/FeldeH19,<br\/>  author = {Felde, Maximilian and Hanika, Tom},<br\/>  booktitle = {ICCS},<br\/>  crossref = {conf\/iccs\/2019},<br\/>  editor = {Endres, Dominik and Alam, Mehwish and Sotropa, Diana},<br\/>  keywords = {itegpub},<br\/>  pages = {57-71},<br\/>  publisher = {Springer},<br\/>  series = {Lecture Notes in Computer Science},<br\/>  title = {Formal Context Generation Using Dirichlet Distributions.},<br\/>  volume = 11530,<br\/>  year = 2019<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-3150e7472057f04f6e9e2da1954671ab\"><p>%0 Conference Paper<br\/>%1 conf\/iccs\/FeldeH19<br\/>%A Felde, Maximilian<br\/>%A Hanika, Tom<br\/>%B ICCS<br\/>%D 2019<br\/>%E Endres, Dominik<br\/>%E Alam, Mehwish<br\/>%E Sotropa, Diana<br\/>%I Springer<br\/>%P 57-71<br\/>%R 10.1007\/978-3-030-23182-8_5<br\/>%T Formal Context Generation Using Dirichlet Distributions.<br\/>%U http:\/\/dblp.uni-trier.de\/db\/conf\/iccs\/iccs2019.html#FeldeH19<br\/>%V 11530<br\/>%@ 978-3-030-23182-8<br\/><\/p><\/div><\/div><\/li><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/phdthesis.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Hanika, T.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">Discovering Knowledge in Bipartite Graphs with Formal Concept Analysis.<\/span><\/span>, (2019). https:\/\/doi.org\/10.17170\/kobra-20190213189.<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-0ce70858b4793650763bee71b3e2a407\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-0ce70858b4793650763bee71b3e2a407\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/dx.doi.org\/10.17170\/kobra-20190213189\" target=\"_blank\">DOI<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/0ce70858b4793650763bee71b3e2a407\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-0ce70858b4793650763bee71b3e2a407\"><p>@phdthesis{phd\/dnb\/Hanika19,<br\/>  author = {Hanika, Tom},<br\/>  keywords = {itegpub},<br\/>  school = {University of Kassel, Germany},<br\/>  title = {Discovering Knowledge in Bipartite Graphs with Formal Concept Analysis.},<br\/>  year = 2019<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-0ce70858b4793650763bee71b3e2a407\"><p>%0 Thesis<br\/>%1 phd\/dnb\/Hanika19<br\/>%A Hanika, Tom<br\/>%D 2019<br\/>%R 10.17170\/kobra-20190213189<br\/>%T Discovering Knowledge in Bipartite Graphs with Formal Concept Analysis.<br\/><\/p><\/div><\/div><\/li><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/inproceedings.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Hanika, T., Koyda, M., Stumme, G.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">Relevant Attributes in Formal Contexts.<\/span><\/span> In: Endres, D., Alam, M., and Sotropa, D. (eds.) ICCS. pp. 102\u2013116. Springer (2019). https:\/\/doi.org\/10.1007\/978-3-030-23182-8_8.<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_url\"><a href=\"http:\/\/dblp.uni-trier.de\/db\/conf\/iccs\/iccs2019.html#HanikaKS19\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-15b11929b97b4ee48f72f21b1bf49b4b\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-15b11929b97b4ee48f72f21b1bf49b4b\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/dx.doi.org\/10.1007\/978-3-030-23182-8_8\" target=\"_blank\">DOI<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/15b11929b97b4ee48f72f21b1bf49b4b\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-15b11929b97b4ee48f72f21b1bf49b4b\"><p>@inproceedings{conf\/iccs\/HanikaKS19,<br\/>  author = {Hanika, Tom and Koyda, Maren and Stumme, Gerd},<br\/>  booktitle = {ICCS},<br\/>  crossref = {conf\/iccs\/2019},<br\/>  editor = {Endres, Dominik and Alam, Mehwish and Sotropa, Diana},<br\/>  keywords = {itegpub},<br\/>  pages = {102-116},<br\/>  publisher = {Springer},<br\/>  series = {Lecture Notes in Computer Science},<br\/>  title = {Relevant Attributes in Formal Contexts.},<br\/>  volume = 11530,<br\/>  year = 2019<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-15b11929b97b4ee48f72f21b1bf49b4b\"><p>%0 Conference Paper<br\/>%1 conf\/iccs\/HanikaKS19<br\/>%A Hanika, Tom<br\/>%A Koyda, Maren<br\/>%A Stumme, Gerd<br\/>%B ICCS<br\/>%D 2019<br\/>%E Endres, Dominik<br\/>%E Alam, Mehwish<br\/>%E Sotropa, Diana<br\/>%I Springer<br\/>%P 102-116<br\/>%R 10.1007\/978-3-030-23182-8_8<br\/>%T Relevant Attributes in Formal Contexts.<br\/>%U http:\/\/dblp.uni-trier.de\/db\/conf\/iccs\/iccs2019.html#HanikaKS19<br\/>%V 11530<br\/>%@ 978-3-030-23182-8<br\/><\/p><\/div><\/div><\/li><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/inproceedings.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">D\u00fcrrschnabel, D., Hanika, T., Stumme, G.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">DimDraw - A Novel Tool for Drawing Concept Lattices.<\/span><\/span> In: Cristea, D., Ber, F.L., Missaoui, R., Kwuida, L., and Sertkaya, B. (eds.) ICFCA (Supplements). pp. 60\u201364. CEUR-WS.org (2019).<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_url\"><a href=\"http:\/\/dblp.uni-trier.de\/db\/conf\/icfca\/icfca2019suppl.html#DurrschnabelHS19\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-2a39286fae6486a078398ca2baefd55b\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-2a39286fae6486a078398ca2baefd55b\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/2a39286fae6486a078398ca2baefd55b\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-2a39286fae6486a078398ca2baefd55b\"><p>@inproceedings{conf\/icfca\/DurrschnabelHS19,<br\/>  author = {D\u00fcrrschnabel, Dominik and Hanika, Tom and Stumme, Gerd},<br\/>  booktitle = {ICFCA (Supplements)},<br\/>  crossref = {conf\/icfca\/2019suppl},<br\/>  editor = {Cristea, Diana and Ber, Florence Le and Missaoui, Rokia and Kwuida, L\u00e9onard and Sertkaya, Baris},<br\/>  keywords = {itegpub},<br\/>  pages = {60-64},<br\/>  publisher = {CEUR-WS.org},<br\/>  series = {CEUR Workshop Proceedings},<br\/>  title = {DimDraw - A Novel Tool for Drawing Concept Lattices.},<br\/>  volume = 2378,<br\/>  year = 2019<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-2a39286fae6486a078398ca2baefd55b\"><p>%0 Conference Paper<br\/>%1 conf\/icfca\/DurrschnabelHS19<br\/>%A D\u00fcrrschnabel, Dominik<br\/>%A Hanika, Tom<br\/>%A Stumme, Gerd<br\/>%B ICFCA (Supplements)<br\/>%D 2019<br\/>%E Cristea, Diana<br\/>%E Ber, Florence Le<br\/>%E Missaoui, Rokia<br\/>%E Kwuida, L\u00e9onard<br\/>%E Sertkaya, Baris<br\/>%I CEUR-WS.org<br\/>%P 60-64<br\/>%T DimDraw - A Novel Tool for Drawing Concept Lattices.<br\/>%U http:\/\/dblp.uni-trier.de\/db\/conf\/icfca\/icfca2019suppl.html#DurrschnabelHS19<br\/>%V 2378<br\/><\/p><\/div><\/div><\/li><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/inproceedings.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Hanika, T., Marx, M., Stumme, G.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">Discovering Implicational Knowledge in Wikidata<\/span>.<\/span> In: Cristea, D., Ber, F.L., and Sertkaya, B. (eds.) Formal Concept Analysis - 15th International Conference, {ICFCA} 2019, Frankfurt, Germany, June 25-28, 2019, Proceedings. pp. 315\u2013323. Springer (2019). https:\/\/doi.org\/10.1007\/978-3-030-21462-3_21.<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/doi.org\/10.1007\/978-3-030-21462-3_21\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-2d7e11d03c808f5ee7f22b106e95c63b\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-2d7e11d03c808f5ee7f22b106e95c63b\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/dx.doi.org\/10.1007\/978-3-030-21462-3_21\" target=\"_blank\">DOI<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/2d7e11d03c808f5ee7f22b106e95c63b\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-2d7e11d03c808f5ee7f22b106e95c63b\"><p>@inproceedings{DBLP:conf\/icfca\/Hanika0S19,<br\/>  author = {Hanika, Tom and Marx, Maximilian and Stumme, Gerd},<br\/>  booktitle = {Formal Concept Analysis - 15th International Conference, {ICFCA} 2019, Frankfurt, Germany, June 25-28, 2019, Proceedings},<br\/>  editor = {Cristea, Diana and Ber, Florence Le and Sertkaya, Baris},<br\/>  keywords = {kdepub},<br\/>  pages = {315--323},<br\/>  publisher = {Springer},<br\/>  series = {Lecture Notes in Computer Science},<br\/>  title = {Discovering Implicational Knowledge in Wikidata},<br\/>  volume = 11511,<br\/>  year = 2019<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-2d7e11d03c808f5ee7f22b106e95c63b\"><p>%0 Conference Paper<br\/>%1 DBLP:conf\/icfca\/Hanika0S19<br\/>%A Hanika, Tom<br\/>%A Marx, Maximilian<br\/>%A Stumme, Gerd<br\/>%B Formal Concept Analysis - 15th International Conference, {ICFCA} 2019, Frankfurt, Germany, June 25-28, 2019, Proceedings<br\/>%D 2019<br\/>%E Cristea, Diana<br\/>%E Ber, Florence Le<br\/>%E Sertkaya, Baris<br\/>%I Springer<br\/>%P 315--323<br\/>%R 10.1007\/978-3-030-21462-3_21<br\/>%T Discovering Implicational Knowledge in Wikidata<br\/>%U https:\/\/doi.org\/10.1007\/978-3-030-21462-3_21<br\/>%V 11511<br\/><\/p><\/div><\/div><\/li><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/inproceedings.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Schaefermeier, B., Hanika, T., Stumme, G.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">Distances for wifi based topological indoor mapping<\/span>.<\/span> In: Proceedings of the 16th {EAI} International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services. {ACM} (2019). https:\/\/doi.org\/10.1145\/3360774.3360780.<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/doi.org\/10.1145%2F3360774.3360780\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-7d27117f9e7285f489478f021ac2c35c\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-7d27117f9e7285f489478f021ac2c35c\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/dx.doi.org\/10.1145\/3360774.3360780\" target=\"_blank\">DOI<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/7d27117f9e7285f489478f021ac2c35c\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-7d27117f9e7285f489478f021ac2c35c\"><p>@inproceedings{Schaefermeier_2019,<br\/>  author = {Schaefermeier, Bastian and Hanika, Tom and Stumme, Gerd},<br\/>  booktitle = {Proceedings of the 16th {EAI} International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services},<br\/>  keywords = {itegpub},<br\/>  month = 11,<br\/>  publisher = {{ACM}},<br\/>  title = {Distances for wifi based topological indoor mapping},<br\/>  year = 2019<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-7d27117f9e7285f489478f021ac2c35c\"><p>%0 Conference Paper<br\/>%1 Schaefermeier_2019<br\/>%A Schaefermeier, Bastian<br\/>%A Hanika, Tom<br\/>%A Stumme, Gerd<br\/>%B Proceedings of the 16th {EAI} International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services<br\/>%D 2019<br\/>%I {ACM}<br\/>%R 10.1145\/3360774.3360780<br\/>%T Distances for wifi based topological indoor mapping<br\/>%U https:\/\/doi.org\/10.1145%2F3360774.3360780<br\/><\/p><\/div><\/div><\/li>\n<\/ul>\n<a class=\"bibsonomycsl_publications-headline-anchor \" name=\"jmp_2018\"><\/a><h3 class=\"bibsonomycsl_publications-headline\" style=\"font-size: 1.1em; font-weight: bold;\">2018<\/h3>\n<ul class=\"bibsonomycsl_publications\"><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/inproceedings.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Doerfel, S., Hanika, T., Stumme, G.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">Clones in Graphs.<\/span><\/span> In: Ceci, M., Japkowicz, N., Liu, J., Papadopoulos, G.A., and Ras, Z.W. (eds.) ISMIS. pp. 56\u201366. Springer (2018). https:\/\/doi.org\/10.1007\/978-3-030-01851-1_6.<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_url\"><a href=\"http:\/\/dblp.uni-trier.de\/db\/conf\/ismis\/ismis2018.html#DoerfelHS18\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-e347f5fa3a991bc49dc2d5f1c1556694\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-e347f5fa3a991bc49dc2d5f1c1556694\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/dx.doi.org\/10.1007\/978-3-030-01851-1_6\" target=\"_blank\">DOI<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/e347f5fa3a991bc49dc2d5f1c1556694\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-e347f5fa3a991bc49dc2d5f1c1556694\"><p>@inproceedings{conf\/ismis\/DoerfelHS18,<br\/>  author = {Doerfel, Stephan and Hanika, Tom and Stumme, Gerd},<br\/>  booktitle = {ISMIS},<br\/>  crossref = {conf\/ismis\/2018},<br\/>  editor = {Ceci, Michelangelo and Japkowicz, Nathalie and Liu, Jiming and Papadopoulos, George A. and Ras, Zbigniew W.},<br\/>  keywords = {kdepub},<br\/>  pages = {56-66},<br\/>  publisher = {Springer},<br\/>  series = {Lecture Notes in Computer Science},<br\/>  title = {Clones in Graphs.},<br\/>  volume = 11177,<br\/>  year = 2018<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-e347f5fa3a991bc49dc2d5f1c1556694\"><p>%0 Conference Paper<br\/>%1 conf\/ismis\/DoerfelHS18<br\/>%A Doerfel, Stephan<br\/>%A Hanika, Tom<br\/>%A Stumme, Gerd<br\/>%B ISMIS<br\/>%D 2018<br\/>%E Ceci, Michelangelo<br\/>%E Japkowicz, Nathalie<br\/>%E Liu, Jiming<br\/>%E Papadopoulos, George A.<br\/>%E Ras, Zbigniew W.<br\/>%I Springer<br\/>%P 56-66<br\/>%R 10.1007\/978-3-030-01851-1_6<br\/>%T Clones in Graphs.<br\/>%U http:\/\/dblp.uni-trier.de\/db\/conf\/ismis\/ismis2018.html#DoerfelHS18<br\/>%V 11177<br\/>%@ 978-3-030-01851-1<br\/><\/p><\/div><\/div><\/li><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/inproceedings.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Hanika, T., Zumbr\u00e4gel, J.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">Towards Collaborative Conceptual Exploration.<\/span><\/span> In: Chapman, P., Endres, D., and Pernelle, N. (eds.) ICCS. pp. 120\u2013134. Springer (2018). https:\/\/doi.org\/10.1007\/978-3-319-91379-7_10.<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_url\"><a href=\"http:\/\/dblp.uni-trier.de\/db\/conf\/iccs\/iccs2018.html#HanikaZ18\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-3a36f6cc1814bf23c75d8d37a2b16024\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-3a36f6cc1814bf23c75d8d37a2b16024\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/dx.doi.org\/10.1007\/978-3-319-91379-7_10\" target=\"_blank\">DOI<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/3a36f6cc1814bf23c75d8d37a2b16024\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-3a36f6cc1814bf23c75d8d37a2b16024\"><p>@inproceedings{conf\/iccs\/HanikaZ18,<br\/>  author = {Hanika, Tom and Zumbr\u00e4gel, Jens},<br\/>  booktitle = {ICCS},<br\/>  crossref = {conf\/iccs\/2018},<br\/>  editor = {Chapman, Peter and Endres, Dominik and Pernelle, Nathalie},<br\/>  keywords = {itegpub},<br\/>  pages = {120-134},<br\/>  publisher = {Springer},<br\/>  series = {Lecture Notes in Computer Science},<br\/>  title = {Towards Collaborative Conceptual Exploration.},<br\/>  volume = 10872,<br\/>  year = 2018<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-3a36f6cc1814bf23c75d8d37a2b16024\"><p>%0 Conference Paper<br\/>%1 conf\/iccs\/HanikaZ18<br\/>%A Hanika, Tom<br\/>%A Zumbr\u00e4gel, Jens<br\/>%B ICCS<br\/>%D 2018<br\/>%E Chapman, Peter<br\/>%E Endres, Dominik<br\/>%E Pernelle, Nathalie<br\/>%I Springer<br\/>%P 120-134<br\/>%R 10.1007\/978-3-319-91379-7_10<br\/>%T Towards Collaborative Conceptual Exploration.<br\/>%U http:\/\/dblp.uni-trier.de\/db\/conf\/iccs\/iccs2018.html#HanikaZ18<br\/>%V 10872<br\/>%@ 978-3-319-91379-7<br\/><\/p><\/div><\/div><\/li>\n<\/ul>\n<a class=\"bibsonomycsl_publications-headline-anchor \" name=\"jmp_2017\"><\/a><h3 class=\"bibsonomycsl_publications-headline\" style=\"font-size: 1.1em; font-weight: bold;\">2017<\/h3>\n<ul class=\"bibsonomycsl_publications\"><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/inproceedings.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Borchmann, D., Hanika, T., Obiedkov, S.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">On the Usability of Probably Approximately Correct Implication Bases.<\/span><\/span> In: Bertet, K., Borchmann, D., Cellier, P., and Ferr\u00e9, S. (eds.) Formal Concept Analysis - 14th International Conference, {ICFCA} 2017, Rennes, France, June 13-16, 2017, Proceedings. pp. 72\u201388. Springer (2017). https:\/\/doi.org\/10.1007\/978-3-319-59271-8_5.<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_url\"><a href=\"http:\/\/dblp.uni-trier.de\/db\/conf\/icfca\/icfca2017.html#BorchmannHO17\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-bfa7746aa81e1a9456966e0b57422172\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-bfa7746aa81e1a9456966e0b57422172\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/dx.doi.org\/10.1007\/978-3-319-59271-8_5\" target=\"_blank\">DOI<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/bfa7746aa81e1a9456966e0b57422172\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-bfa7746aa81e1a9456966e0b57422172\"><p>@inproceedings{conf\/icfca\/BorchmannHO17,<br\/>  author = {Borchmann, Daniel and Hanika, Tom and Obiedkov, Sergei},<br\/>  booktitle = {Formal Concept Analysis - 14th International Conference, {ICFCA} 2017, Rennes, France, June 13-16, 2017, Proceedings},<br\/>  crossref = {conf\/icfca\/2017},<br\/>  editor = {Bertet, Karell and Borchmann, Daniel and Cellier, Peggy and Ferr\u00e9, S\u00e9bastien},<br\/>  keywords = {itegpub},<br\/>  pages = {72-88},<br\/>  publisher = {Springer},<br\/>  series = {Lecture Notes in Computer Science},<br\/>  title = {On the Usability of Probably Approximately Correct Implication Bases.},<br\/>  volume = 10308,<br\/>  year = 2017<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-bfa7746aa81e1a9456966e0b57422172\"><p>%0 Conference Paper<br\/>%1 conf\/icfca\/BorchmannHO17<br\/>%A Borchmann, Daniel<br\/>%A Hanika, Tom<br\/>%A Obiedkov, Sergei<br\/>%B Formal Concept Analysis - 14th International Conference, {ICFCA} 2017, Rennes, France, June 13-16, 2017, Proceedings<br\/>%D 2017<br\/>%E Bertet, Karell<br\/>%E Borchmann, Daniel<br\/>%E Cellier, Peggy<br\/>%E Ferr\u00e9, S\u00e9bastien<br\/>%I Springer<br\/>%P 72-88<br\/>%R 10.1007\/978-3-319-59271-8_5<br\/>%T On the Usability of Probably Approximately Correct Implication Bases.<br\/>%U http:\/\/dblp.uni-trier.de\/db\/conf\/icfca\/icfca2017.html#BorchmannHO17<br\/>%V 10308<br\/>%@ 978-3-319-59271-8<br\/><\/p><\/div><\/div><\/li><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/inbook.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Borchmann, D., Hanika, T.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">Individuality in Social Networks<\/span>.<\/span> In: Missaoui, R., Kuznetsov, S.O., and Obiedkov, S. (eds.) Formal Concept Analysis of Social Networks. pp. 19\u201340. Springer International Publishing, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-64167-6_2.<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_export bibsonomycsl_abstract\"><a rel=\"abs-2c7e6be27e1bee2ca4fc5c1fff91fdac\"  href=\"#\">Abstract<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/doi.org\/10.1007\/978-3-319-64167-6_2\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-2c7e6be27e1bee2ca4fc5c1fff91fdac\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-2c7e6be27e1bee2ca4fc5c1fff91fdac\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/dx.doi.org\/10.1007\/978-3-319-64167-6_2\" target=\"_blank\">DOI<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/2c7e6be27e1bee2ca4fc5c1fff91fdac\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_abstract\" style=\"display:none;\" id=\"abs-2c7e6be27e1bee2ca4fc5c1fff91fdac\">We consider individuality in bi-modal social networks, a facet that has not been considered before in the mathematical analysis of social networks. We use methods from formal concept analysis to develop a natural definition for individuality, and provide experimental evidence that this yields a meaningful approach for additional insights into the nature of social networks.<\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-2c7e6be27e1bee2ca4fc5c1fff91fdac\"><p>@inbook{Borchmann2017,<br\/>  abstract = {We consider individuality in bi-modal social networks, a facet that has not been considered before in the mathematical analysis of social networks. We use methods from formal concept analysis to develop a natural definition for individuality, and provide experimental evidence that this yields a meaningful approach for additional insights into the nature of social networks.},<br\/>  address = {Cham},<br\/>  author = {Borchmann, Daniel and Hanika, Tom},<br\/>  booktitle = {Formal Concept Analysis of Social Networks},<br\/>  editor = {Missaoui, Rokia and Kuznetsov, Sergei O. and Obiedkov, Sergei},<br\/>  keywords = {itegpub},<br\/>  pages = {19--40},<br\/>  publisher = {Springer International Publishing},<br\/>  title = {Individuality in Social Networks},<br\/>  year = 2017<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-2c7e6be27e1bee2ca4fc5c1fff91fdac\"><p>%0 Book Section<br\/>%1 Borchmann2017<br\/>%A Borchmann, Daniel<br\/>%A Hanika, Tom<br\/>%B Formal Concept Analysis of Social Networks<br\/>%C Cham<br\/>%D 2017<br\/>%E Missaoui, Rokia<br\/>%E Kuznetsov, Sergei O.<br\/>%E Obiedkov, Sergei<br\/>%I Springer International Publishing<br\/>%P 19--40<br\/>%R 10.1007\/978-3-319-64167-6_2<br\/>%T Individuality in Social Networks<br\/>%U https:\/\/doi.org\/10.1007\/978-3-319-64167-6_2<br\/>%X We consider individuality in bi-modal social networks, a facet that has not been considered before in the mathematical analysis of social networks. We use methods from formal concept analysis to develop a natural definition for individuality, and provide experimental evidence that this yields a meaningful approach for additional insights into the nature of social networks.<br\/>%@ 978-3-319-64167-6<br\/><\/p><\/div><\/div><\/li>\n<\/ul>\n<a class=\"bibsonomycsl_publications-headline-anchor \" name=\"jmp_2016\"><\/a><h3 class=\"bibsonomycsl_publications-headline\" style=\"font-size: 1.1em; font-weight: bold;\">2016<\/h3>\n<ul class=\"bibsonomycsl_publications\"><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border\"><img decoding=\"async\" onmouseover=\"javascript:showtrail('https:\/\/www.kde.cs.uni-kassel.de\/en\/hanika\/publications?action=preview&userName=tomhanika&intraHash=8af414e45f306527e8316ac681fe7f08&fileName=Some+Experimental+Results+on+Randomly+Generating+Formal+Contexts.pdf&size=LARGE')\" onmouseout=\"javascript:hidetrail()\" class=\"bibsonomycsl_preview\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/en\/hanika\/publications?action=preview&userName=tomhanika&intraHash=8af414e45f306527e8316ac681fe7f08&fileName=Some+Experimental+Results+on+Randomly+Generating+Formal+Contexts.pdf&size=SMALL&doc%5B\u0000GuzzleHttp\\Psr7\\Stream\u0000stream%5D=Resource id #124&doc%5B\u0000GuzzleHttp\\Psr7\\Stream\u0000seekable%5D=1&doc%5B\u0000GuzzleHttp\\Psr7\\Stream\u0000readable%5D=1&doc%5B\u0000GuzzleHttp\\Psr7\\Stream\u0000writable%5D=1&doc%5B\u0000GuzzleHttp\\Psr7\\Stream\u0000uri%5D=php:\/\/temp&\" \/><\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Borchmann, D., Hanika, T.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">Some Experimental Results on Randomly Generating Formal Contexts.<\/span><\/span> In: Huchard, M. and Kuznetsov, S. (eds.) CLA. pp. 57\u201369. CEUR-WS.org (2016).<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_url\"><a href=\"http:\/\/dblp.uni-trier.de\/db\/conf\/cla\/cla2016.html#BorchmannH16\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-8af414e45f306527e8316ac681fe7f08\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-8af414e45f306527e8316ac681fe7f08\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/8af414e45f306527e8316ac681fe7f08\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><span class=\"bibsonomycsl_download\"><a href=\"https:\/\/www.kde.cs.uni-kassel.de\/en\/hanika\/publications?action=download&userName=tomhanika&intraHash=8af414e45f306527e8316ac681fe7f08&fileName=Some+Experimental+Results+on+Randomly+Generating+Formal+Contexts.pdf\" target=\"_blank\">Download<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-8af414e45f306527e8316ac681fe7f08\"><p>@inproceedings{conf\/cla\/BorchmannH16,<br\/>  author = {Borchmann, Daniel and Hanika, Tom},<br\/>  booktitle = {CLA},<br\/>  crossref = {conf\/cla\/2016},<br\/>  editor = {Huchard, Marianne and Kuznetsov, Sergei},<br\/>  keywords = {itegpub},<br\/>  pages = {57-69},<br\/>  publisher = {CEUR-WS.org},<br\/>  series = {CEUR Workshop Proceedings},<br\/>  title = {Some Experimental Results on Randomly Generating Formal Contexts.},<br\/>  volume = 1624,<br\/>  year = 2016<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-8af414e45f306527e8316ac681fe7f08\"><p>%0 Conference Paper<br\/>%1 conf\/cla\/BorchmannH16<br\/>%A Borchmann, Daniel<br\/>%A Hanika, Tom<br\/>%B CLA<br\/>%D 2016<br\/>%E Huchard, Marianne<br\/>%E Kuznetsov, Sergei<br\/>%I CEUR-WS.org<br\/>%P 57-69<br\/>%T Some Experimental Results on Randomly Generating Formal Contexts.<br\/>%U http:\/\/dblp.uni-trier.de\/db\/conf\/cla\/cla2016.html#BorchmannH16<br\/>%V 1624<br\/><\/p><\/div><\/div><\/li><li class=\"bibsonomycsl_pubitem\"><div class=\"bibsonomycsl_preview_border bibsonomycsl_preview_thumb\">\n                                        <span>\n                                            <img decoding=\"async\" class=\"bibsonomycsl_preview\" style=\"z-index: 1;\" src=\"https:\/\/www.kde.cs.uni-kassel.de\/wp-content\/plugins\/bibsonomy-csl\/img\/entrytypes\/inproceedings.jpg\" \/>\n                                        <\/span>\n                                 <\/div><div class=\"bibsonomycsl_entry\"><div class=\"csl-bib-body\">\n  <div class=\"csl-entry\"><div class=\"csl-left-margin\"><span style=\"display: none;\">1.<\/span><\/div><div class=\"csl-right-inline\"><span class=\"csl-author\">Atzmueller, M., Hanika, T., Stumme, G., Schaller, R., Ludwig, B.: <\/span><span class=\"csl-title\"><span class=\"csl-title\">{Social Event Network Analysis: Structure, Preferences, and Reality}<\/span>.<\/span> In: Proc. IEEE\/ACM ASONAM. IEEE Press, Boston, MA, USA (2016).<\/div><\/div>\n<\/div><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.kde.cs.uni-kassel.de\/atzmueller\/paper\/atzmueller-social-event-analysis-asonam16-preprint.pdf\" target=\"_blank\">URL<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_bibtex\"><a rel=\"bib-9d3966d8cee2f5cebeeaa0144469cb12\" href=\"#\">BibTeX<\/a><\/span><span class=\"bibsonomycsl_export bibsonomycsl_endnote\"><a rel=\"end-9d3966d8cee2f5cebeeaa0144469cb12\" href=\"#\">EndNote<\/a><\/span><span class=\"bibsonomycsl_url\"><a href=\"https:\/\/www.bibsonomy.org\/bibtex\/9d3966d8cee2f5cebeeaa0144469cb12\/tomhanika\" target=\"_blank\">BibSonomy<\/a><\/span><div style=\"clear: left\"> <\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_bibtex\" style=\"display:none;\" id=\"bib-9d3966d8cee2f5cebeeaa0144469cb12\"><p>@inproceedings{langeNachtFCA,<br\/>  address = {Boston, MA, USA},<br\/>  author = {Atzmueller, Martin and Hanika, Tom and Stumme, Gerd and Schaller, Richard and Ludwig, Bernd},<br\/>  booktitle = {Proc. IEEE\/ACM ASONAM},<br\/>  keywords = {itegpub},<br\/>  publisher = {IEEE Press},<br\/>  title = {{Social Event Network Analysis: Structure, Preferences, and Reality}},<br\/>  year = 2016<br\/>}<br\/><\/p><\/div><div class=\"bibsonomycsl_collapse bibsonomycsl_pub_endnote\" style=\"display:none;\" id=\"end-9d3966d8cee2f5cebeeaa0144469cb12\"><p>%0 Conference Paper<br\/>%1 langeNachtFCA<br\/>%A Atzmueller, Martin<br\/>%A Hanika, Tom<br\/>%A Stumme, Gerd<br\/>%A Schaller, Richard<br\/>%A Ludwig, Bernd<br\/>%B Proc. IEEE\/ACM ASONAM<br\/>%C Boston, MA, USA<br\/>%D 2016<br\/>%I IEEE Press<br\/>%T {Social Event Network Analysis: Structure, Preferences, and Reality}<br\/>%U https:\/\/www.kde.cs.uni-kassel.de\/atzmueller\/paper\/atzmueller-social-event-analysis-asonam16-preprint.pdf<br\/><\/p><\/div><\/div><\/li><\/ul>","protected":false},"excerpt":{"rendered":"<p>List of publications and preprints by Tom Hanika 2025 1.Hille, T., Hanika, T.: Incomplete Formal Contexts and Their Intrinsic Dimension. In: Cellier, P., Ganter, B., and Missaoui, R. (eds.) SpringerLink. pp. 342\u2013358. Springer, Cham, Switzerland<a class=\"moretag\" href=\"https:\/\/www.kde.cs.uni-kassel.de\/en\/hanika\/publications\"> Read more&hellip;<\/a><\/p>\n","protected":false},"author":10,"featured_media":0,"parent":137,"menu_order":4,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-4127","page","type-page","status-publish","hentry"],"translation":{"provider":"WPGlobus","version":"3.0.2","language":"en","enabled_languages":["de","en"],"languages":{"de":{"title":true,"content":true,"excerpt":false},"en":{"title":false,"content":false,"excerpt":false}}},"_links":{"self":[{"href":"https:\/\/www.kde.cs.uni-kassel.de\/en\/wp-json\/wp\/v2\/pages\/4127","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.kde.cs.uni-kassel.de\/en\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.kde.cs.uni-kassel.de\/en\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.kde.cs.uni-kassel.de\/en\/wp-json\/wp\/v2\/users\/10"}],"replies":[{"embeddable":true,"href":"https:\/\/www.kde.cs.uni-kassel.de\/en\/wp-json\/wp\/v2\/comments?post=4127"}],"version-history":[{"count":5,"href":"https:\/\/www.kde.cs.uni-kassel.de\/en\/wp-json\/wp\/v2\/pages\/4127\/revisions"}],"predecessor-version":[{"id":6981,"href":"https:\/\/www.kde.cs.uni-kassel.de\/en\/wp-json\/wp\/v2\/pages\/4127\/revisions\/6981"}],"up":[{"embeddable":true,"href":"https:\/\/www.kde.cs.uni-kassel.de\/en\/wp-json\/wp\/v2\/pages\/137"}],"wp:attachment":[{"href":"https:\/\/www.kde.cs.uni-kassel.de\/en\/wp-json\/wp\/v2\/media?parent=4127"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}