schmidtAndreas Schmidt
Raum 0445 B 0440
Universität Kassel
Fachbereich Elektrotechnik/Informatik
Fachgebiet Wissensverarbeitung
Wilhelmshöher Allee 73
34121 Kassel
Tel.: +49 561 804-6254 6253
Fax.: +49 561 804-6259
Email: schmidt@cs.uni-kassel.de

Projects

fee

Teaching

Supervised Theses

  • Florian Fassing: Exceptional Model Mining zur Entdeckung Abnormaler Communities
  • Linus Bunk: Extraktion und Analyse bipartiter Graphen in DBpedia

Winter Semester 2018/2019

Summer Semester 2018

Winter Semester 2017/2018

Summer Semester 2017

Winter Semester 2016/2017

Summer Semester 2016

Winter Semester 2015/2016

Summer Semester 2015

Publications

    2018

    • Schmidt, A., Stumme, G.: Prominence and Dominance in Networks. In: Faron Zucker, C., Ghidini, C., Napoli, A., and Yannick, T. (eds.) Proceedings of the 21th International Conference on Knowledge Engineering and Knowledge Management (EKAW). pp. 370-385. Springer (2018).
      BibTeX EndNote URL

    2017

    • Atzmueller, M., Schmidt, A., Kloepper, B., Arnu, D.: HypGraphs: An Approach for Analysis and Assessment of Graph-Based and Sequential Hypotheses. New Frontiers in Mining Complex Patterns. Postproceedings NFMCP 2016. Springer Verlag, Berlin/Heidelberg, Germany (2017).
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    • Atzmueller, M., Arnu, D., Schmidt, A.: Anomaly Detection and Structural Analysis in Industrial Production Environments. Proc. International Data Science Conference (IDSC 2017). , Salzburg, Austria (2017).
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    • Atzmueller, M., Arnu, D., Schmidt, A.: Anomaly Analytics and Structural Assessment in Process Industries. Proc. Annual Machine Learning Conference of the Benelux (Benelearn 2017). Eindhoven University of Technology, Eindhoven, The Netherlands (2017).
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    • Atzmueller, M., Hayat, N., Schmidt, A., Klöpper, B.: Explanation-Aware Feature Selection using Symbolic Time Series Abstraction: Approaches and Experiences in a Petro-Chemical Production Context. Proc. IEEE International Conference on Industrial Informatics (INDIN). IEEE Press, Boston, MA, USA (2017).
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    2016

    • Atzmueller, M., Mollenhauer, D., Schmidt, A.: Big Data Analytics Using Local Exceptionality Detection. Enterprise Big Data Engineering, Analytics, and Management. IGI Global, Hershey, PA, USA (2016).
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    • Schmidt, A., Atzmueller, M., Hollender, M.: Data Preparation for Big Data Analytics: Methods & Experiences. Enterprise Big Data Engineering, Analytics, and Management. IGI Global, Hershey, PA, USA (2016).
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    • Atzmueller, M., Schmidt, A., Kibanov, M.: DASHTrails: An Approach for Modeling and Analysis of Distribution-Adapted Sequential Hypotheses and Trails. Proc. WWW 2016 (Companion). IW3C2 / ACM (2016).
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    • Atzmueller, M., Schmidt, A., Arnu, D.: Sequential Modeling and Structural Anomaly Analytics in Industrial Production Environments. Proc. LWA 2016 (KDML Special Track). University of Potsdam, Potsdam, Germany (2016).
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    • Atzmueller, M., Kloepper, B., Mawla, H.A., Jäschke, B., Hollender, M., Graube, M., Arnu, D., Schmidt, A., Heinze, S., Schorer, L., Kroll, A., Stumme, G., Urbas, L.: Big Data Analytics for Proactive Industrial Decision Support: Approaches & First Experiences in the Context of the FEE Project. atp edition. 58, (2016).
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    • Atzmueller, M., Schmidt, A., Kloepper, B., Arnu, D.: HypGraphs: An Approach for Modeling and Comparing Graph-Based and Sequential Hypotheses. Proc. ECML-PKDD Workshop on New Frontiers in Mining Complex Patterns (NFMCP). , Riva del Garda, Italy (2016).
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    2015

    • Schmidt, A., Atzmueller, M., Stumme, G.: The FEE Project: Introduction and First Insights. Proc. UIS Workshop (2015).
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