Oren Sar Shalom
Dietmar Jannach
Ido Guy
ABSTRACT
Research in the area of recommender systems is largely focused on the value such a system creates for the users, by helping them finding items they are interested in. This is usually done by learning to rank the recommendable items based on their assumed relevance for each user. The implicit underlying goal often is that this personalization positively affects users in different positive ways, e.g., by making their search and decision processes easier or by helping them discover new things [3].
- Himan Abdollahpouri, Gediminas Adomavicius, Robin Burke, Ido Guy, Dietmar Jannach, Toshihiro Kamishima, Jan Krasnodebski, and Luiz Augusto Pizzato. 2019. Beyond Personalization: Research Directions in Multistakeholder Recommendation. CoRR abs/1905.01986 (2019). http://arxiv.org/abs/1905.01986Google Scholar
- Shir Frumerman, Guy Shani, Bracha Shapira, and Oren Sar Shalom. 2019. Are All Rejected Recommendations Equally Bad?: Towards Analysing Rejected Recommendations. In Proceedings of the 27th ACM Conference on User Modeling, Adaptation and Personalization. ACM, 157--165. Google ScholarDigital Library
- Dietmar Jannach and Gediminas Adomavicius. 2016. Recommendations with a Purpose. In Proceedings of the 10th ACM Conference on Recommender Systems (RecSys '16). 7--10. Google ScholarDigital Library
- Oren Sar Shalom, Noam Koenigstein, Ulrich Paquet, and Hastagiri P Vanchinathan. 2016. Beyond collaborative filtering: The list recommendation problem. In Proceedings of the 25th international conference on world wide web. International World Wide Web Conferences Steering Committee, 63--72. Google ScholarDigital Library
- J Ben Schafer, Joseph Konstan, and John Riedl. 1999. Recommender systems in e-commerce. In Proceedings of the 1st ACM conference on Electronic commerce. ACM, 158--166. Google ScholarDigital Library
Index Terms
- First workshop on the impact of recommender systems at ACM RecSys 2019
Recommendations
Second Workshop on the Impact of Recommender Systems at ACM RecSys ’20
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