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CoupledCF: Learning Explicit and Implicit User-item Couplings in Recommendation for Deep Collaborative Filtering
2018
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence
Non-IID recommender system discloses the nature of recommendation and has shown its potential in improving recommendation quality and addressing issues such as sparsity and cold start. It leverages existing work that usually treats users/items as in- dependent while ignoring the rich couplings within and between users and items, leading to limited performance improvement. In reality, users/items are related with various couplings existing within and between users and items, which may better ex-
doi:10.24963/ijcai.2018/509
dblp:conf/ijcai/ZhangCZLS18
fatcat:j56loxrh3bae5jc5fh4lbkz74q