Benedikt Loepp, M. Sc.

While studying the bachelor program of Applied Computer Science at the University of Duisburg-Essen, Benedikt Loepp started to work as a student assistant in 2010, among others, in the Interactive Systems group. After having received his bachelor’s degree in 2011, Benedikt joined the group as a researcher in March 2012. Since then, he has been administrative coordinator for Computer Science in the MINTroduce project, supporting study beginners at the university and being responsible for the program’s preliminary courses.

After he finished the university’s master program of Applied Computer Science in 2013 (with distinction), he finally became a full member of the Interactive Systems group. His research focuses on the field of recommender systems, in particular, preference elicitation and interactive recommending approaches. Besides, Benedikt was involved in the ColognE-mobil project part II, where he was responsible for developing smart navigation solutions for intermodal mobility chains. Furthermore, he contributed to several research developments, e.g. Blended Recommending, TagMF, and the Archaeological Sandbox. He also enjoys his teaching activities, including, among others, a lecture on Recommender Systems.

Since 2014, Benedikt is webmaster of the official ACM RecSys website, and regularly serves as web chair for the conference.

Phone +49 (203) 379-3946
Fax +49 (203) 379-3557
Office LF 285
LSF view

Selected publications

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


Interactive Recommending with Tag-Enhanced Matrix Factorization (TagMF)

Impact of Item Consumption on Assessment of Recommendations in User Studies

Recommending Running Routes: Framework and Demonstrator

Understanding Latent Factors Using a GWAP

Ein Online-Spiel zur Benennung latenter Faktoren in Empfehlungssystemen

Explaining Recommendations by Means of User Reviews

Eine Sandbox zur physisch-virtuellen Exploration von Ausgrabungsstätten

Sequential User-based Recurrent Neural Network Recommendations

Enhancing an Interactive Recommendation System with Review-based Information Filtering

Empirische Bedarfsanalyse zur intermodalen Navigation und dem Einsatz von Informationssystemen zur Förderung ihrer Attraktivität

On User Awareness in Model-Based Collaborative Filtering Systems

A 3D Item Space Visualization for Presenting and Manipulating User Preferences in Collaborative Filtering

Interactive Recommending: Framework, State of Research and Future Challenges

All 25 publication

Main research topics

Recent teaching

Administrative and scientific functions

Selected review activities