Professorship for Information Systems, in particular Machine Learning
Organisational unit: Professoship
Main research areas
Research
We are interested in statistical machine learning with a focus on spatiotemporal problems, such as user navigation on the web, adaptive testing and adaptive learning environments, and the coordination of football players on the pitch. While we mainly focus on basic research, we also collaborate with selected partners in academia, sports and industry in different projects.
Teaching
Our teaching focuses on introductory/advanced machine learning and data mining as well as basic statistics. We regularly offer courses in the Management & Data Science Master and the Information Systems Bachelor programs. Exemplary courses comprise Deep Learning (Data Science), Statistics (Information Systems), and Machine Learning & Data Mining (Engineering).
- 2019
- Published
Zur empirischen Beforschung des mBooks Belgien: Die Chancen eines Methodenmix
Schreiber, W., Wagner, W., Trautwein, U. & Brefeld, U., 10.2019, Das Geschichtsschulbuch: Lehren – Lernen – Forschen . Kühberger, C., Bernhard, R. & Bramann, C. (eds.). Münster: Waxmann Verlag, p. 57-80 24 p. (Salzburger Beiträge zur Lehrer/innen/bildung; vol. 6).Research output: Contributions to collected editions/works › Contributions to collected editions/anthologies › Research › peer-review
- Published
Personalized Transaction Kernels for Recommendation Using MCTS
Tavakol, M., Joppen, T., Brefeld, U. & Fürnkranz, J., 01.09.2019, KI 2019: Advances in Artificial Intelligence - 42nd German Conference on AI, Proceedings. Benzmüller, C. & Stuckenschmidt, H. (eds.). Wiesbaden: Springer, p. 338-352 15 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11793 LNAI).Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
- Published
Predicting the Difficulty of Exercise Items for Dynamic Difficulty Adaptation in Adaptive Language Tutoring
Pandarova, I., Schmidt, T., Hartig, J., Boubekki, A., Jones, R. D. & Brefeld, U., 15.08.2019, In: International Journal of Artificial Intelligence in Education. 29, 3, p. 342-367 26 p.Research output: Journal contributions › Journal articles › Research › peer-review
- Published
Machine Learning and Data Mining for Sports Analytics: 5th International Workshop, MLSA 2018, colocated with ECML/PKDD 2018, Dublin, Ireland, September 10, 2018, Proceedings
Brefeld, U. (Editor), Davis, J. (Editor), Van Haaren, J. (Editor) & Zimmermann, A. (Editor), 05.04.2019, Springer Nature AG. 179 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11330 LNAI)Research output: Books and anthologies › Collected editions and anthologies › Research
- Published
Learning to Rate Player Positioning in Soccer
Dick, U. & Brefeld, U., 01.03.2019, In: Big Data. 7, 1, p. 71-82 12 p.Research output: Journal contributions › Journal articles › Research › peer-review
- Published
Reformstudie Belgien: eine Effektstudie zur Einführung von kompetenzorientiertem Rahmenplan und mBook
Schreiber, W., Trautwein, U., Wagner, W. & Brefeld, U., 01.02.2019, Geschichtsdidaktischer Zwischenhalt: Beiträge aus der Tagung "Kompetent machen für ein Leben in, mit und durch Geschichte" in Eichstätt vom November 2017. Schreiber, W., Ziegler, B. & Kühberger, C. (eds.). 1. ed. Münster: Waxmann Verlag, p. 161-174 14 p. 2Research output: Contributions to collected editions/works › Contributions to collected editions/anthologies › Research
- Published
Frame-based Optimal Design
Mair, S., Rudolph, Y., Closius, V. & Brefeld, U., 23.01.2019, Machine learning and knowledge discovery in databases: European Conference, ECML PKDD 2018, Dublin, Ireland, September 10-14, 2018 : proceedings. Berlingerio, M., Bonchi, F., Gärtner, T., Hurley, N. & Ifrim, G. (eds.). Cham: Springer Nature AG, Vol. 2. p. 447-463 17 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11052 LNAI).Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
- Published
Probabilistic movement models and zones of control
Brefeld, U., Lasek, J. & Mair, S., 15.01.2019, In: Machine Learning. 108, 1, p. 127-147 21 p.Research output: Journal contributions › Journal articles › Research › peer-review
- Published
Foreword to applied data science, demo, and nectar tracks
Brefeld, U., Curry, E., Daly, E., Macnamee, B., Marascu, A. & Pinelli, F., 01.01.2019, Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2018, Dublin, Ireland, September 10-14, 2018 : proceedings. Brefeld, U., Curry, E., Daly, E., Macnamee, B., Marascu, A. & Pinelli, F. (eds.). Cham: Springer, Vol. 3. p. V-VI 2 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11053).Research output: Contributions to collected editions/works › Other › Research
- Published
Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2018, Dublin, Ireland, September 10-14, 2018, Proceedings - Part III
Brefeld, U. (Editor), Curry , E. (Editor), Daly, E. (Editor), MacNamee, B. (Editor), Marascu, A. (Editor), Pinelli , F. (Editor), Berlingerio, M. (Editor) & Hurley, N. (Editor), 2019, Cham: Springer. 706 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11054 LNAI)Research output: Books and anthologies › Collected editions and anthologies › Research