Prof. Dr.-Ing. Jürgen Ziegler

Jürgen Ziegler is a full professor in the Department of Computer Science and Applied Cognitive Science at the University of Duisburg-Essen where he directs the Interactive Systems Research Group. Prior to joining the University, he was head of the Competence Center for Software Technology and Interactive Systems at the Fraunhofer Institute for Industrial Engineering in Stuttgart.

Jürgen Ziegler holds a diploma degree in electrical engineering and biocybernetics from the University of Karlsruhe and a doctoral degree from the University of Stuttgart. His main research interests lie in the areas of human-computer interaction, information visualisation and context-adaptive systems. Current projects of his group focus on context-aware recommender systems, visual interfaces for Semantic Web data, playful social interaction, and adaptive driver assistance in cars.


Jürgen Ziegler is editor in chief of the German HCI journal i-com: Zeitschrift für interaktive und kooperative Medien. Find out more on the scope of the journal.


Phone +49 (203) 379-2270
Fax +49 (203) 379-3557
Office LF 291
LSF view

Selected publications

Effects of argumentative explanation types on the perception of review-based recommendations

Distribution Sliders: Visualizing Data Distributions in Range Selection Sliders

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

Explaining Recommendations by Means of Aspect-Based Transparent Memories


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

Challenges in User-Centered Engineering of AI-based Interactive Systems

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

Towards Interactive Recommending in Model-based Collaborative Filtering Systems

How Can They Know That? A Study of Factors Affecting the Creepiness of Recommendations

Augmented-Reality-Enhanced Product Comparison in Physical Retailing

Integration of Dialog-based Product Advisors into Filter Systems

Feature-driven interactive recommendations and explanations with collaborative filtering approach

To explain or not to explain: the effects of personal characteristics when explaining feature-based recommendations in different domains

All 230 publication