Collaborative Filtering Model Based on Time Context for IPTV Live Recommendation
With the increase in the number of IPTV live channels, the users are faced with the problem of information overload and the degraded users’ quality of experience (QoE). This paper combines the time context information with the collaborative filtering recommendation algorithm to design the IPTV live recommendation system (RS). Finally, the fusion recommendation model is proposed and its accuracy rate has a great improvement.
KeywordsLive recommendation system Time context Collaborative filtering Fusion model
This work is partly supported by the National Natural Science Foundation of China (Grants No. 61571240, 61671474), the Jiangsu Science Fund for Excellent Young Scholars (No. BK20170089), the ZTE program ‘‘The Prediction of Wireline Network Malfunction and Traffic Based on Big Data’’ and the Priority Academic Program Development of Jiangsu Higher Education Institutions.
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