Tim Donkers, M. Sc.

After finishing his master’s program in 2017, Tim Donkers joined the group as a full member. His main research interests are recommender systems, deep learning and explainable AI.

Phone +49 (203) 379-2716
Fax +49 (203) 379-3557
Office LF 289
LSF view


Let Me Explain: Impact of Personal and Impersonal Explanations on Trust in Recommender Systems

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

Argumentation-based explanations in recommender systems: Conceptual framework and empirical results

Trust-Related Effects of Expertise and Similarity Cues in Human-Generated Recommendations

Explaining Recommendations by Means of User Reviews

Sequential User-based Recurrent Neural Network Recommendations

Towards Understanding Latent Factors and User Profiles by Enhancing Matrix Factorization with Tags

ConceptCloud -Entwicklung einer Applikation zur Unterstützung von Reflexionsprozessen im Online-Lernportal Go-Lab

Merging Latent Factors and Tags to Increase Interactive Control of Recommendations

Main research topic