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.

Mail
Phone +49 (203) 379-2716
Fax +49 (203) 379-3557
Office LF 289
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Publications

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

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