Multi-feature behavior relationship for multi-behavior recommendation

HIGHLIGHTS

  • who: Xiaodong Mu and colleagues from the Xi`an Research Institute of High Technology, Xi`an, China have published the research: Multi-Feature Behavior Relationship for Multi-Behavior Recommendation, in the Journal: (JOURNAL)
  • what: The authors propose a Multi-Feature Behavior Relationship for MultiBehavior (MFBR) framework which models the multi-behavior problem from both sequence structure and graph structure perspectives for user preference prediction of target behaviors. The authors propose a multi-behavior recommendation framework, MFBR, that learns higherorder behavioral interaction patterns on user-item multi-relationship graphs and captures sequence information among behaviors in . . .

     

    Logo ScioWire Beta black

    If you want to have access to all the content you need to log in!

    Thanks :)

    If you don't have an account, you can create one here.

     

Scroll to Top

Add A Knowledge Base Question !

+ = Verify Human or Spambot ?