Set2setRank: Collaborative Set to Set Ranking for Implicit Feedback based Recommendation

@article{Chen2021Set2setRankCS,
  title={Set2setRank: Collaborative Set to Set Ranking for Implicit Feedback based Recommendation},
  author={Lei Chen and Le Wu and Kun Zhang and Richang Hong and Meng Wang},
  journal={Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval},
  year={2021}
}
  • Lei Chen, Le Wu, +2 authors Meng Wang
  • Published 2021
  • Computer Science
  • Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval
As users often express their preferences with binary behavior data~(implicit feedback), such as clicking items or buying products, implicit feedback based Collaborative Filtering~(CF) models predict the top ranked items a user might like by leveraging implicit user-item interaction data. For each user, the implicit feedback is divided into two sets: an observed item set with limited observed behaviors, and a large unobserved item set that is mixed with negative item behaviors and unknown… Expand

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