Peter Brusilovsky
Marco de Gemmis
Alexander Felfernig
Pasquale Lops
Martijn C. Willemsen
Abstract
The 10th edition of the Joint Workshop on Interfaces and Human Decision Making for Recommender Systems was held as part of the 17th ACM Conference on Recommender Systems (RecSys), the premier international forum for the presentation of new research results, systems and techniques in the broad field of recommender systems. The workshop was organized as a hybrid event: the physical session took place on September 18th at the venue of the main conference, Singapore, with the possibility for authors to present remotely. The IntRS workshop brings together an interdisciplinary community of researchers and practitioners who share research on new recommender systems (informed by psychology), including new design technologies and evaluation methodologies, and aim to identify critical challenges and emerging topics in the field. This year we focused particularly on topics related to Human-Centered AI, Explainability of decision-making models, User-adaptive XAI systems, which are becoming more and more popular in the last years, especially in domains where recommended options might have ethical and legal impacts on users. The integration of XAI with recommender systems is crucial for enhancing their transparency, interpretability, and accountability. This topic attracted a lot of interest from the community, as demonstrated by the fact that several workshop papers proposed methods for recommendation explanations.
Date: 18 September 2023.
Website: https://intrs2023.wordpress.com.
- Peter Brusilovsky, Marco de Gemmis, Alexander Felfernig, Pasquale Lops, John O'Donovan, Giovanni Semeraro, and Martijn C. Willemsen. Interfaces and human decision making for recommender systems. In Fourteenth ACM Conference on Recommender Systems, pages 613--618. ACM, 2020. URL https://doi.org/10.1145%2F3383313.3411539. Google Scholar
Digital Library
- Sebastian Lubos, Thi Ngoc Trang Tran, Seda Polat Erdeniz, Merfat El Mansi, Alexander Felfernig, Manfred Wundara, and Gerhard Leitner. Concentrating on the Impact: Consequence-based Explanations in Recommender Systems. In Proceedings of the 10th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS 2023), pages 63--73. CEUR-WS.org, 2023.Google Scholar
- Ayoub El Majjodi, Alain D. Starke, Mehdi Elahi, and Christoph Trattner. The Interplay between Food Knowledge, Nudges, and Preference Elicitation Methods Determines the Evaluation of a Recipe Recommender System. In Proceedings of the 10th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS 2023), pages 1--18. CEUR-WS.org, 2023.Google Scholar
- Ahtsham Manzoor, Wanling Cai, and Dietmar Jannach. Factors Influencing the Perceived Meaningfulness of System Responses in Conversational Recommendation. In Proceedings of the 10th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS 2023), pages 19--34. CEUR-WS.org, 2023.Google Scholar
- Itallo Silva, Alan Said, Leandro Balby Marinho, and Martijn Willemsen. Leveraging Large Language Models for Recommendation and Explanation. In Proceedings of the 10th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS 2023), pages 74--81. CEUR-WS.org, 2023.Google Scholar
- Alain D. Starke, Kimia Emami, Andrea Makarová, and Bruce Ferwerda. Using Visual and Linguistic Framing to Support Sustainable Decisions in an Online Store. In Proceedings of the 10th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS 2023), pages 53--62. CEUR-WS.org, 2023.Google Scholar
- Maxwell Szymanski, Cristina Conati, Vero Vanden Abeele, and Katrien Verbert. Designing and Personalising Hybrid Multi-Modal Health Explanations for Lay Users. In Proceedings of the 10th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS 2023), pages 35--52. CEUR-WS.org, 2023.Google Scholar
Index Terms
- Report on the 10th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS 2023) at ACM RecSys 2023
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