Dr.-Ing. Benedikt Loepp

Benedikt received his bachelor’s (2011) and master’s degree (2013, with distinction) in Applied Computer Science at the University of Duisburg-Essen. While studying, he started to work as a student assistant, among others, in the Interactive Systems group. Benedikt joined the group as a researcher in March 2012. From then to 2020, he was administrative coordinator for Computer Science in the MINTroduce project, in which he supported study beginners and was responsible for the program’s preliminary courses.

In 2013, Benedikt became a full member of the Interactive Systems group. His research focuses on the field of recommender systems, in particular, preference elicitation, interactive recommending and user studies. At the intersection of these topics, he also started his PhD studies, which, among others, led to several research developments, e.g. Blended Recommending and TagMF. In parallel, Benedikt was involved in the ColognE-mobil project part II, where he was responsible for developing smart navigation solutions for intermodal mobility chains, as well as in other research developments, e.g. the Archaeological Sandbox and several GWAPs. In March 2021, Benedikt finished his PhD studies and received the degree of Dr.-Ing. (summa cum laude).

Benedikt also enjoys his teaching activities, including a lecture on Recommender Systems. Since 2014, he has been webmaster of the official ACM RecSys website. Until 2020, he also served as web chair for the conference. Moreover, he regularly serves as a committee member and reviewer for a variety of journals and conferences. Most recently, Benedikt co-founded the GI group on User-centered AI and became a member of the Global Young Faculty VII.

Thesis

Benedikt Loepp: Interactive Methods for Model-based Collaborative Filtering Recommender Systems (Dr.-Ing.)

Contact

Mail	benedikt [dot] loepp [at] uni-due [dot] de
Web	https://benedikt.loepp.eu
Phone	+49 (203) 379-3946
Fax	+49 (203) 379-3557
Office	LF 285
LSF	view

Selected publications

Towards Multi-Method Support for Product Search and Recommending

Kleemann, T., Loepp, B., & Ziegler, J. (to appear). In UMAP ’22: Adjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization. ACM.

Modeling User Interaction at the Convergence of Filtering Mechanisms, Recommender Algorithms and Advisory Components

Kleemann, T., Wagner, M., Loepp, B., & Ziegler, J. (2021). Mensch Und Computer 2021 – Tagungsband, 531–543.

On the Convergence of Intelligent Decision Aids

Loepp, B. (2021). Mensch Und Computer 2021 – Workshopband.

Interactive Methods for Model-based Collaborative Filtering Recommender Systems

Loepp, B. (2021). [PhD thesis, University of Duisburg-Essen].

Empfehlungssysteme

Ziegler, J., & Loepp, B. (2020). In T. Kollmann (Ed.), Handbuch Digitale Wirtschaft (pp. 717–741). Springer Gabler.

On the Use of Feature-based Collaborative Explanations: An Empirical Comparison of Explanation Styles

Naveed, S., Loepp, B., & Ziegler, J. (2020). ExUM ’20: Proceedings of the International Workshop on Transparent Personalization Methods Based on Heterogeneous Personal Data, 226–232.

Measuring the Impact of Recommender Systems – A Position Paper on Item Consumption in User Studies

Loepp, B., & Ziegler, J. (2019). Proceedings of the 1st Workshop on Impact of Recommender Systems (ImpactRS ’19).

Impact of Consuming Suggested Items on the Assessment of Recommendations in User Studies on Recommender Systems

Loepp, B., Donkers, T., Kleemann, T., & Ziegler, J. (2019). Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI ’19), 6201–6205.