文件名称：KGAT：Knowledge Graph Attention Network for Recommendation.pdf
文件大小：1.36MB
文件格式：PDF
更新时间：2022-08-29 08:57:25
KG
Toprovidemoreaccurate,diverse,andexplainablerecommendation, it is compulsory to go beyond modeling user-item interactions andtakesideinformationintoaccount.Traditionalmethodslike factorizationmachine(FM)castitasasupervisedlearningproblem, whichassumeseachinteractionasanindependentinstancewith side information encoded. Due to the overlook of the relations amonginstancesoritems(e.g., thedirectorofamovieisalsoan actorofanothermovie),thesemethodsareinsufficienttodistillthe collaborativesignalfromthecollectivebehaviorsofusers.