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Multimedia Tools and Applications

, Volume 47, Issue 1, pp 31–48 | Cite as

3PRS: a personalized popular program recommendation system for digital TV for P2P social networks

  • Jui-Hung ChangEmail author
  • Chin-Feng Lai
  • Yueh-Min Huang
  • Han-Chieh Chao
Article

Abstract

Digital TV channels require users to spend more time to choose their favorite TV programs. Electronic Program Guides (EPG) cannot be used to find popular TV programs. Hence, this paper proposes a personalized Digital Video Broadcasting — Terrestrial(DVB-T) Digital TV program recommendation system for P2P social networks. From the DVB-T signal, we obtain EPG of TV programs. The frequency and duration of the programs that users have watched are used to extract programs that users are interested in. The information is collected and weighted by Information Retrieval (IR). The program information is then clustered by k-means. Clusters of users are also grouped by k-means to find cluster relationships. In each group, we decide the most popular program in the group according to the program weight of the channel. When a new user begins to watch the TV program, the K-Nearest Neighbor (kNN) classification method is used to determine the user’s predicted cluster label. Then, our system recommends popular programs in the predicted cluster and similar clusters.

Keywords

Digital video broadcasting-terrestrial (DVB-T) Electronic program guide (EPG) Information retrieval (IR) K-nearest neighbo (kNN) k-means 

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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Jui-Hung Chang
    • 1
    Email author
  • Chin-Feng Lai
    • 1
  • Yueh-Min Huang
    • 1
  • Han-Chieh Chao
    • 2
    • 3
  1. 1.Department of Engineering ScienceNational Cheng Kung UniversityTainanPeople’s Republic of China
  2. 2.Institute of Computer Science & Information Engineering and Department of Electronic EngineeringNational Ilan UniversityI-LanPeople’s Republic of China
  3. 3.Department of Electrical EngineeringNational Dong Hwa UniversityHualienPeople’s Republic of China

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