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A Context-Aware Movie Preference Model Using a Bayesian Network for Recommendation and Promotion

  • Chihiro Ono
  • Mori Kurokawa
  • Yoichi Motomura
  • Hideki Asoh
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4511)

Abstract

This paper proposes a novel approach for constructing users’ movie preference models using Bayesian networks. The advantages of the constructed preference models are 1) consideration of users’ context in addition to users’ personality, 2) multiple applications, such as recommendation and promotion. Data acquisition process through a WWW questionnaire survey and a Bayesian network model construction process using the data are described. The effectiveness of the constructed model in terms of recommendation and promotion is also demonstrated through experiments.

Keywords

Bayesian Network Recommender System Model Construction Preference Model Collaborative Filter 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Chihiro Ono
    • 1
  • Mori Kurokawa
    • 1
  • Yoichi Motomura
    • 1
  • Hideki Asoh
    • 1
  1. 1.KDDI R&D Labs, Inc., Keio University, AIST 

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