Propagation-aware Social Recommendation by Transfer Learning

  title={Propagation-aware Social Recommendation by Transfer Learning},
  author={Haodong Chang and Ya-Chi Chu},
Social-aware recommendation approaches have been recognized as an effective way to solve the data sparsity issue of traditional recommender systems. The assumption behind is that the knowledge in social user-user connections can be shared and transferred to the domain of user-item interactions, whereby to help learn user preferences. However, most existing approaches merely adopt the first-order connections among users during transfer learning, ignoring those connections in higher orders. We… 

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