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AIMED- A Personalized TV Recommendation System

  • Shang H. Hsu
  • Ming-Hui Wen
  • Hsin-Chieh Lin
  • Chun-Chia Lee
  • Chia-Hoang Lee
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4471)

Abstract

Previous personalized DTV recommendation systems focus only on viewers’ historical viewing records or demographic data. This study proposes a new recommending mechanism from a user oriented perspective. The recommending mechanism is based on user properties such as Activities, Interests, Moods, Experiences, and Demographic information—AIMED. The AIMED data is fed into a neural network model to predict TV viewers’ program preferences. Evaluation results indicate that the AIMED model significantly increases recommendation accuracy and decreases prediction errors compared to the conventional model.

Keywords

TV program recommendation system predictor personal information lifestyle activity interest mood 

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Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Shang H. Hsu
    • 1
  • Ming-Hui Wen
    • 1
  • Hsin-Chieh Lin
    • 1
  • Chun-Chia Lee
    • 1
  • Chia-Hoang Lee
    • 2
  1. 1.Department of Industrial Engineering and Management 
  2. 2.Department of Computer Science, National Chiao Tung University, 1001 Ta Hsueh Road, HsinchuTaiwan

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