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Towards Equivalent Transformation of User Preferences in Cross Domain Recommendation
[article]
2022
arXiv
pre-print
Cross domain recommendation (CDR) is one popular research topic in recommender systems. This paper focuses on a popular scenario for CDR where different domains share the same set of users but no overlapping items. The majority of recent methods have explored the shared-user representation to transfer knowledge across domains. However, the idea of shared-user representation resorts to learn the overlapped features of user preferences and suppresses the domain-specific features. Other works try
arXiv:2009.06884v2
fatcat:aeyzv4kotbakrirf4mdhqt6luy