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MORS 2021: 1st Workshop on Multi-Objective Recommender Systems

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Allison Chaney, and

Babak LoniAuthors Info & Claims

RecSys '21: Proceedings of the 15th ACM Conference on Recommender Systems

September 2021

Pages 787 - 788

https://doi.org/10.1145/3460231.3470936

Published: 13 September 2021 Publication History

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Abstract

Historically, the main criterion for a successful recommender system was the relevance of the recommended items to the user. In other words, the only objective for the recommendation algorithm was to learn user’s preferences for different items and generate recommendations accordingly. However, real-world recommender systems are well beyond a simple objective and often need to take into account multiple objectives simultaneously. These objectives can be either from the users’ perspective or they could come from other stakeholders such as item providers or any party that could be impacted by the recommendations. Such multi-objective and multi-stakeholder recommenders present unique challenges and these challenges were the focus of the MORS workshop.

References

[1]

Robin Burke, Himan Abdollahpouri, Edward C Malthouse, KP Thai, and Yongfeng Zhang. 2019. Recommendation in multistakeholder environments. In Proceedings of the 13th ACM Conference on Recommender Systems. 566–567.

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[2]

Robin Burke, Gediminas Adomavicius, Ido Guy, Jan Krasnodebski, Luiz Pizzato, Yi Zhang, and Himan Abdollahpouri. 2017. Vams 2017: Workshop on value-aware and multistakeholder recommendation. In Proceedings of the Eleventh ACM Conference on Recommender Systems. 378–379.

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Cited By

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Deldjoo YJannach DBellogin ADifonzo AZanzonelli D(2023)Fairness in recommender systems: research landscape and future directionsUser Modeling and User-Adapted Interaction10.1007/s11257-023-09364-z34:1(59-108)Online publication date: 24-Apr-2023
https://dl.acm.org/doi/10.1007/s11257-023-09364-z

MORS 2021: 1st Workshop on Multi-Objective Recommender Systems
1. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals

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RecSys '21: Proceedings of the 15th ACM Conference on Recommender Systems

September 2021

883 pages

ISBN:9781450384582

DOI:10.1145/3460231

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

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Published: 13 September 2021

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RecSys '21

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RecSys '21: Fifteenth ACM Conference on Recommender Systems

September 27 - October 1, 2021

Amsterdam, Netherlands

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Overall Acceptance Rate 254 of 1,295 submissions, 20%

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RecSys '24

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sigchi

18th ACM Conference on Recommender Systems

October 14 - 18, 2024

Bari , Italy

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Deldjoo YJannach DBellogin ADifonzo AZanzonelli D(2023)Fairness in recommender systems: research landscape and future directionsUser Modeling and User-Adapted Interaction10.1007/s11257-023-09364-z34:1(59-108)Online publication date: 24-Apr-2023
https://dl.acm.org/doi/10.1007/s11257-023-09364-z

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Recommendations

MORS 2022: The Second Workshop on Multi-Objective Recommender Systems

A survey of recommender systems with multi-objective optimization

Multi-objective optimization with recommender systems: A systematic review

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