Recommender Systems are becoming an inherent part of today's Internet. They can be found anywhere from e-commerce platforms (eBay, Amazon) to music or movie streaming (Spotify, Netflix), social media (Facebook, Instagram, TikTok), travel platforms (Booking.com, Expedia), and much more. Whether a recommendation is successful or not can rely on multiple objectives such as user satisfaction, business value, and societal issues. In addition, the long-term happiness (along with short-term excitements and delight) of the users is critical for a recommender system to be considered successful. MORS workshop brings together researchers and practitioners to discuss the importance of these aspects of recommender systems and find ways to develop algorithms to build multi-objective recommenders and also evaluation metrics to assess their success.
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CITATION STYLE
Abdollahpouri, H., Sahebi, S., Elahi, M., Mansoury, M., Loni, B., Nazari, Z., & Dimakopoulou, M. (2022). MORS 2022: The Second Workshop on Multi-Objective Recommender Systems. In RecSys 2022 - Proceedings of the 16th ACM Conference on Recommender Systems (pp. 658–660). Association for Computing Machinery, Inc. https://doi.org/10.1145/3523227.3547410