University of Kassel
Knowledge & Data Engineering Group

Knowledge & Data Engineering Group (KDE), EECS, University of Kassel

The research unit Knowledge & Data Engineering at the Department of Electrical Engineering/Computer Science is developing methods for knowledge discovery and representation (approximation and exploration of knowledge, order structures in knowledge, ontology learning) and for the analysis of (social) networks and related knowledge processes (metrics in networks, anomaly detection, characterization of social networks). Our focus is on the exact algebraic modelling of structures in knowledge and networks. Our research on foundations in order and lattice theory, description logics, graph theory and ontologies is complemented by applications in social media and scientometrics. The research unit Knowledge & Data Engineering is member in theInterdisciplinary Research Center for Information System Design (ITeG) and the International Centre for Higher Education Research (INCHER Kassel) at the University of Kassel and in theL3S Research Center.

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Our latest publications:

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    Hanika, T., Hirth, J.: Knowledge cores in large formal contexts. Annals of Mathematics and Artificial Intelligence. (2022).
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    Schäfermeier, B., Stumme, G., Hanika, T.: Mapping Research Trajectories, https://arxiv.org/abs/2204.11859, (2022).
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    Hanika, T., Schneider, F.M., Stumme, G.: Intrinsic dimension of geometric data sets. Tohoku Mathematical Journal. 74, 23–52 (2022).
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    Stubbemann, M., Stumme, G.: LG4AV: Combining Language Models and Graph Neural Networks for Author Verification. (2021).
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    Felde, M., Stumme, G.: Triadic Exploration and Exploration with Multiple Experts. In: Braud, A., Buzmakov, A., Hanika, T., and Le Ber, F. (eds.) Formal Concept Analysis. pp. 175–191. Springer International Publishing, Cham (2021).
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    Schaefermeier, B., Stumme, G., Hanika, T.: Topic space trajectories. Scientometrics. 126, 5759–5795 (2021).
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    Dürrschnabel, D., Stumme, G.: Force-Directed Layout of Order Diagrams using Dimensional Reduction, http://arxiv.org/abs/2102.02684, (2021).
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    Stubbemann, M., Stumme, G.: The Mont Blanc of Twitter: Identifying Hierarchies of Outstanding Peaks in Social Networks. arXiv preprint arXiv:2110.13774. (2021).
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    Stubbemann, L., Dürrschnabel, D., Refflinghaus, R.: Neural Networks for Semantic Gaze Analysis in XR Settings. ACM Symposium on Eye Tracking Research and Applications. ACM (2021).
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    Dürrschnabel, D., Hanika, T., Stubbemann, M.: FCA2VEC: Embedding Techniques for Formal Concept Analysis. Presented at the (2021).
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    Hanika, T., Hirth, J.: Quantifying the Conceptual Error in Dimensionality Reduction. 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. 105–118. Springer (2021).
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    Hanika, T., Hirth, J.: Exploring Scale-Measures of Data Sets. 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. 261–269. Springer (2021).
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    Koyda, M., Stumme, G.: Boolean Substructures in Formal Concept Analysis. ICFCA: International Conference on Formal Concept Analysis. pp. 38–53. Springer (2021).
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  • 1.
    Dürrschnabel, D., Stumme, G.: Force-Directed Layout of Order Diagrams Using Dimensional Reduction. In: Braud, A., Buzmakov, A., Hanika, T., and Le Ber, F. (eds.) Formal Concept Analysis. pp. 224–240. Springer International Publishing, Cham (2021).
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    Dürrschnabel, D., Koyda, M., Stumme, G.: Attribute Selection Using Contranominal Scales. In: Braun, T., Gehrke, M., Hanika, T., and Hernandez, N. (eds.) Graph-Based Representation and Reasoning. pp. 127–141. Springer International Publishing, Cham (2021).
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    Draude, C., Gruhl, C., Hornung, G., Kropf, J., Lamla, J., Leimeister, J.M., Sick, B., Stumme, G.: Social Machines. Informatik Spektrum. (2021).
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    Koopmann, T., Stubbemann, M., Kapa, M., Paris, M., Buenstorf, G., Hanika, T., Hotho, A., Jäschke, R., Stumme, G.: Proximity dimensions and the emergence of collaboration: a HypTrails study on German AI research. Scientometrics. (2021).
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    Schaefermeier, B., Stumme, G., Hanika, T.: Topological Indoor Mapping through WiFi Signals. (2021).
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    Schäfermeier, B., Stumme, G., Hanika, T.: Towards Explainable Scientific Venue Recommendations, http://arxiv.org/abs/2109.11343, (2021).
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    Braun, T., Gehrke, M., Hanika, T., Hernandez, N. eds.: Graph-Based Representation and Reasoning - 26th International Conference on Conceptual Structures, ICCS 2021, Virtual Event, September 20-22, 2021, Proceedings. Springer (2021).
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