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Collaborative Filtering Model Based on Time Context for IPTV Live Recommendation

  • Zhengying Hu
  • Yun Gao
  • Xin WeiEmail author
  • Fang Zhou
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 834)

Abstract

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.

Keywords

Live recommendation system Time context Collaborative filtering Fusion model 

Notes

Acknowledgements

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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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.College of Telecommunications and Information Engineering, Nanjing University of Posts and TelecommunicationsNanjingChina
  2. 2.National Engineering Research Center for Communication and Information Technology (NUPT)NanjingChina
  3. 3.School of Electrical and Information EngineeringAnhui University of TechnologyMaanshanChina

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