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

MORS 2021: 1st Workshop on Multi-Objective Recommender Systems
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MORS 2021:第一届多目标推荐系统研讨会

DOI:
10.1145/3460231.3470936
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发表时间:
2021
期刊:
RecSys '21: Proceedings of the 15th ACM Conference on Recommender Systems
影响因子:
--
通讯作者:
Loni, Babak
Loni, Babak
中科院分区:
--
文献类型:
--
作者:
Abdollahpouri, Himan;Elahi, Mehdi;Mansoury, Masoud;Sahebi, Shaghayegh;Nazari, Zahra;Chaney, Allison;Loni, Babak

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从历史上看,成功的推荐系统的主要标准是推荐项目与用户的相关性。换句话说,推荐算法的唯一目标是学习用户对不同项目的偏好,并相应地生成推荐。然而,现实世界中的推荐系统远远不只是一个简单的目标,而且经常需要同时考虑多个目标。这些目标既可以从用户的角度出发,也可以来自其他利益攸关方,如项目提供者或可能受到建议影响的任何一方。这种多目标和多方利益攸关方推荐人提出了独特的挑战,而这些挑战是MORS讲习班的重点。
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.
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影响因子: --
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