Computer Science ›› 2019, Vol. 46 ›› Issue (6A): 502-506.

• Big Data & Data Mining • Previous Articles     Next Articles

User Interest Recommendation Model Based on Context Awareness

LI Jian-jun, HOU Yue, YANG Yu   

  1. School of Computer and Information Engineering,Harbin University of Commerce,Harbin 150028,China
  • Online:2019-06-14 Published:2019-07-02

Abstract: With the development and popularization of electronic commerce and Internet,the user-oriented personalized recommendation is getting more and more attention,the traditional user interest models only consider theuser’s own behavior towards the project,while ignoring the user’s scene at that time.Aiming at this problem,this paper proposed a user interest model based on scene perception,combined the user’s browsing behavior with the situational factors,deeply mined user interest in the project from two aspects,cleared user awareness of the project,thus accurate clustered for users,and target users based on user clustering results were recommended.Experimental results show that the accuracy of this model recommendation is higher than that of other traditional recommendation algorithms.It can better mine users’ interests,adapt to the changes of users’ interests,better solve the problem that users have no way to choose a lot of information,and improve users’ satisfaction.Therefore,it is necessary to excavate the hidden information of users from multiple perspectives so as to better provide personalized recommendations for users.

Key words: User clustering, Context awareness, Personalized recommendation, User interest

CLC Number: 

  • TP301
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