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.

i-com

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.

Contact

Mail
Phone +49 (203) 379-2270
Fax +49 (203) 379-3557
Office LF 291
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Selected publications

Featuristic: An interactive hybrid system for generating explainable recommendations – Beyond system accuracy

Naveed, S., & Ziegler, J. (2020). Proceedings of the 7th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems, 14–25.

Exploring chatbot user interfaces for mood measurement: A study of validity and user experience

Torkamaan, H., & Ziegler, J. (2020). Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers, 135–138.

Distribution sliders: Visualizing data distributions in range selection sliders

Kleemann, T., & Ziegler, J. (2020). Conference on "Mensch Und Computer", 67–78.

In-Store Augmented Reality-Enabled Product Comparison and Recommendation

Álvarez Márquez, O. J., & Ziegler, J. (2020). RecSys ’20: 14th ACM Conference on Recommender Systems ; Virtual Event, Brazil, 180–189.

Leveraging Arguments in User Reviews for Generating and Explaining Recommendations

Donkers, T., & Ziegler, J. (2020). Datenbank-Spektrum, 20(2), 181–187.

Exploring Mental Models for Transparent and Controllable Recommender Systems: A Qualitative Study

Ngo, T. P., Kunkel, J., & Ziegler, J. (2020). UMAP 2020 - Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization, 183–191.

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.

Effects of Argumentative Explanation Types on the Perception of Review-Based Recommendations

Hernandez-Bocanegra, D. C., Donkers, T., & Ziegler, J. (2020). Adjunct Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization (UMAP ’20 Adjunct), 219–225.

Argumentative explanations for recommendations - Effect of display style and profile transparency

Hernandez-Bocanegra, D. C., & Ziegler, J. (2020). Proceedings of the Mensch Und Computer 2020 Workshop on User-Centered Artificial Intelligence (UCAI 2020).

Explaining Recommendations by Means of Aspect-Based Transparent Memories

Donkers, T., Kleemann, T., & Ziegler, J. (2020). In F. Paternò & N. Oliver (Eds.), Proceedings of the 25th International Conference on Intelligent User Interfaces (pp. 166–176). The Association for Computing Machinery.

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).

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

Ziegler, J. (2019). In B. Weyers & J. Bowen (Eds.), Joint Proceedings HCI Engineering 2019 – Methods and Tools for Advanced Interactive Systems and Integration of Multiple Stakeholder Viewpoints co-located with 11th ACM SIGCHI Symposium on Engineering Interactive Computing Systems (EICS 2019) (Vol. 2503, pp. 51–55).

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.

Towards Interactive Recommending in Model-based Collaborative Filtering Systems

Loepp, B., & Ziegler, J. (2019). Proceedings of the 13th ACM Conference on Recommender Systems (RecSys ’19), 546–547.

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

Torkamaan, H., Barbu, C.-M., & Ziegler, J. (2019). In T. Bogers & A. Said (Eds.), Proceedings of the 13th ACM Conference on Recommender Systems (pp. 423–427). ACM.

All 236 publication

Main research topics

Modelling and Understanding User Behavior

Social Media Engineering

Additional information