Towards Equivalent Transformation of User Preferences in Cross Domain Recommendation

Understand

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.