Yuan Ma (former member)

Yuan studied Computer Engineering at the University of Duisburg-Essen, focusing on machine learning and deep learning. He did an internship in the Bosch Research Center for Automatic Optical Inspection (Image Processing) and wrote his master thesis at the Volkswagen Group Innovation for Autonomous Driving (3D Object Detection). Yuan joined the interactive system group in 2020 as a PhD candidate, mainly researching the application of AI-based methods in interactive systems and recommender systems. He completed his PhD in January 2025.

Thesis

  • Yuan Ma: Meta-Intents: Interaction Preferences in Conversational Recommender Systems (Dr.-Ing.)

Contact

Mail

Publications

Meta-Intents: Interaction Preferences in Conversational Recommender Systems

Ma, Y. (2025). [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.

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.

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.

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.

Meta-Intents in Conversational Recommender Systems

Ma, Y., Donkers, T., Kleemann, T., & Ziegler, J. (2022). In V. Anelli, P. Basile, & G. De Melo (Eds.), Proceedings of the Fourth Knowledge-aware and Conversational Recommender Systems Workshop co-located with 16th ACM Conference on Recommender Systems (RecSys 2022) (Vol. 3294, pp. 81–90). RWTH Aachen.

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.

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.

What works and what does not: Classifier and feature analysis for argument mining

Aker, A., Sliwa, A., Ma, Y., Liu, R., Borad, N., Ziyaei, S. F., & Ghbadi, M. (2017). Proceedings of the 4th Workshop on Argument Mining, 91–96.