Publications related to Meta-Intents in Conversational Recommender Systems
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.
Harnessing Latent Space Semantics for Enhanced Interpretability of Recommender Systems in Item Retrieval and Online Communication Dynamics
Donkers, T. (2024). [PhD thesis].
Investigating meta-intents: user interaction preferences in conversational recommender systems
Ma, Y., & Ziegler, J. (2024). User Modeling and User-Adapted Interaction, in press.
From explanations to human-AI co-evolution: Charting trajectories towards future user-centric AI
Ziegler, J., & Donkers, T. (2024). i-Com: Journal of Interactive Media, 23(2), 263–272.
The Effect of Proactive Cues on the Use of Decision Aids in Conversational Recommender Systems
Ma, Y., & Ziegler, J. (2024). In The Association for Computing Machinery (ACM) (Ed.), Adjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization (UMAP Adjunct ’24) (pp. 305–315). ACM.
From explanations to human-AI co-evolution: Charting trajectories towards future user-centric AI
Ziegler, J., & Donkers, T. (2024). i-Com: Journal of Interactive Media, in press.
The Effect of Proactive Cues on the Use of Decision Aids in Conversational Recommender Systems
Ma, Y., & Ziegler, J. (2024). Adjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization.
De-sounding echo chambers: Simulation-based analysis of polarization dynamics in social networks
Donkers, T., & Ziegler, J. (2023). Online Social Networks and Media, 37-38.
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.
ConceptCloud -Entwicklung einer Applikation zur Unterstützung von Reflexionsprozessen im Online-Lernportal Go-Lab
Angenendt, K., Bormann, J., Donkers, T., Goebel, T., Kizina, A., Kleemann, T., Michael, L., Raja, H., Sachs, F., Schneegass, C., Sinzig, L.-M., Steffen, J., Manske, S., Hecking, T., & Hoppe, U. H. (2015). In S. Rathmayer & H. Pongratz (Eds.), Proceedings of DeLFI Workshops 2015 (Vol. 1443, pp. 132–135). CEUR-WS.
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.
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.
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.
An integrated approach for transparent, multi-level decision support in interactive recommender systems
Kleemann, T. (2024). [PhD thesis].
Leveraging Arguments in User Reviews for Generating and Explaining Recommendations
Donkers, T., & Ziegler, J. (2020). Datenbank-Spektrum, 20(2), 181–187.
Integration of Dialog-based Product Advisors into Filter Systems
Kleemann, T., & Ziegler, J. (2019). Proceedings of the Conference on Mensch Und Computer, 67–77.
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.
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.
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.
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.
Argumentative Explanations for Recommendations Based on Reviews
Hernandez Bocanegra, D. C. (2022). [PhD thesis, University of Duisburg-Essen].
Argumentation-based explanations in recommender systems: Conceptual framework and empirical results
Naveed, S., Donkers, T., & Ziegler, J. (2018). UMAP 2018 - Adjunct Publication of the 26th Conference on User Modeling, Adaptation and Personalization, 293–298.
Explaining Recommendations by Means of User Reviews
Donkers, T., Loepp, B., & Ziegler, J. (2018). Proceedings of the 1st Workshop on Explainable Smart Systems (ExSS ’18).
Sequential User-based Recurrent Neural Network Recommendations
Donkers, T., Loepp, B., & Ziegler, J. (2017). Proceedings of the 11th ACM Conference on Recommender Systems (RecSys ’17), 152–160.
The Dual Echo Chamber: Modeling Social Media Polarization for Interventional Recommending
Donkers, T., & Ziegler, J. (2021). Fifteenth ACM Conference on Recommender Systems, 12–22.
Distribution sliders: Visualizing data distributions in range selection sliders
Kleemann, T., & Ziegler, J. (2020). Conference on "Mensch Und Computer", 67–78.
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.
Towards Understanding Latent Factors and User Profiles by Enhancing Matrix Factorization with Tags
Donkers, T., Loepp, B., & Ziegler, J. (2016). Poster Proceedings of the 10th ACM Conference on Recommender Systems (RecSys ’16).
Merging Latent Factors and Tags to Increase Interactive Control of Recommendations
Donkers, T., Loepp, B., & Ziegler, J. (2015). Poster Proceedings of the 9th ACM Conference on Recommender Systems (RecSys ’15).