Timm Kleemann (former member)

Timm Kleemann joined the Interactive Systems group in 2016. He started working as a student assistant and, after receiving his master’s degree in 2017, is now continuing as a researcher. His research focuses in the field of interactive recommending systems, user interfaces and user experience. Timm left the group at the end of 2022, but continues his work as an external PhD student.

Thesis

  • Timm Kleemann: An Integrated Approach for Transparent, Multi-Level Decision Support in Interactive Recommender Systems (Dr.-Ing.)

Contact

Mail

Selected publications

An integrated approach for transparent, multi-level decision support in interactive recommender systems

Kleemann, T. (2024). [PhD thesis].

Harnessing Latent Space Semantics for Enhanced Interpretability of Recommender Systems in Item Retrieval and Online Communication Dynamics

Donkers, T. (2024). [PhD thesis].

Blending Conversational Product Advisors and Faceted Filtering in a Graph-Based Approach

Kleemann, T., & Ziegler, J. (2023). In J. Abdelnour Nocera, Kristı́n Lárusdóttir Marta, H. Petrie, A. Piccinno, & M. Winckler (Eds.), Human-Computer Interaction – INTERACT 2023 : 19th IFIP TC13 International Conference, York, UK, August 28 – September 1, 2023, Proceedings, Part III (Vol. 14144, pp. 137–159). Springer Nature Switzerland.

An Instrument for measuring users’ meta-intents

Ma, Y., Donkers, T., Kleemann, T., & Ziegler, J. (2023). In J. Gwizdka & S. Y. Rieh (Eds.), CHIIR ’23: Proceedings of the 2023 Conference on Human Information Interaction and Retrieval (pp. 290–302). ACM.

Psychological User Characteristics and Meta-Intents in a Conversational Product Advisor

Ma, Y., Kleemann, T., & Ziegler, J. (2022). Proceedings of the 9th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems, 3222, 18–32.

Meta-Intents in Conversational Recommender Systems

Yuan, M., Donkers, T., Kleemann, T., & Jürgen, Z. (2022). Proceedings of the 4th Edition of Knowledge-Aware and Conversational Recommender Systems (KaRS) Workshop @ RecSys 2022.

Towards Multi-Method Support for Product Search and Recommending

Kleemann, T., Loepp, B., & Ziegler, J. (2022). Adjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization (UMAP ’22), 74–79.

Mixed-Modality Interaction in Conversational Recommender Systems

Ma, Y., Kleemann, T., & Ziegler, J. (2021). Proceedings of the 8th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems, 2948, 21–37.

Modeling User Interaction at the Convergence of Filtering Mechanisms, Recommender Algorithms and Advisory Components

Kleemann, T., Wagner, M., Loepp, B., & Ziegler, J. (2021). Mensch Und Computer 2021 – Tagungsband, 531–543.

Distribution sliders: Visualizing data distributions in range selection sliders

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

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.

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.

Integration of Dialog-based Product Advisors into Filter Systems

Kleemann, T., & Ziegler, J. (2019). Proceedings of the Conference on Mensch Und Computer, 67–77.

Interactive Recommending with Tag-Enhanced Matrix Factorization (TagMF)

Loepp, B., Donkers, T., Kleemann, T., & Ziegler, J. (2019). International Journal of Human Computer Studies, 121, 21–41.

Impact of Item Consumption on Assessment of Recommendations in User Studies

Loepp, B., Donkers, T., Kleemann, T., & Ziegler, J. (2018). Proceedings of the 12th ACM Conference on Recommender Systems (RecSys ’18), 49–53.

All 16 publication