The Research of Broadcast Television Program Recommendation Technology Based on User Clustering
Xin Wang, Jianbo Liu, JianPingChai · 2016
Aiming at the information overload caused by rich resources of Broadcast Television programs, this paper puts forward Broadcast Television Programs Recommendation Technology based on user clustering. According to user rating data and programs broadcasting data, we cluster users by the improved K-MEANS algorithm, divide the users with similar viewing preference into the same community groups, and generate the programs candidate list by the users' viewing preference and trust level in the community, in order to recommend programs to the users. Through formula verification and experimental evaluation, we describe that the effect of Broadcast Television programs recommendation technology based on user clustering is better than the global recommendation technology.