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Recommendation System of IPTV TV Program Using Ontology and K-means Clustering

  • Jongwoo Kim
  • Eungju Kwon
  • Yongsuk Cho
  • Sanggil Kang
Part of the Communications in Computer and Information Science book series (CCIS, volume 151)

Abstract

In this paper we introduce a recommendation system for recommending preferred TV genres for each viewer, using ontology technique and K-means clustering algorithm. The algorithm is developed based on the personal VOD viewing history. First, the viewing history is built in an ontology which is able to achieve inference process through a query. In the list of users, each item and class obtain the probability of preference of VODs and then the information is used for building the ontology. From the ontology we select each user’s preferred VODs using K-means algorithm. In the experimental section, we show the feasibility of our algorithm using real TV viewing data.

Keywords

clustering K-means ontology recommendation of genres 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Jongwoo Kim
    • 1
  • Eungju Kwon
    • 1
  • Yongsuk Cho
    • 2
  • Sanggil Kang
    • 1
  1. 1.Department of Computer Science and Information EngineeringInha UniversityIncheonKorea
  2. 2.Department of Electronic EngineeringKonyang UniversityChungcheongnam-doKorea

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