GroupLens: applying collaborative filtering to Usenet news
Communications of the ACM
A Framework for Collaborative, Content-Based and Demographic Filtering
Artificial Intelligence Review - Special issue on data mining on the Internet
A personalized television listings service
Communications of the ACM
User interfaces for digital television: a navigator case study
AVI '00 Proceedings of the working conference on Advanced visual interfaces
A Digital Television Navigator
Multimedia Tools and Applications
Learning Collaborative Information Filters
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
A personalized recommendation system for electronic program guide
AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
TVGuide2.0: applying the Web2.0 fundamentals to IDTV
Multimedia Tools and Applications
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With the growing popularity of digital broadcasting, viewers the have chance to watch various programs. However, they may have trouble choosing just one among many programs. To solve this problem, various studies about EPG and Personalized EPG have been performed. In this study, we reviewed previous studies about EPG, Personalized EPG and the results of recommendation evaluations, and evaluated PEPG system's recommendation, which was implemented as working prototype. We collected preference information about categorys and channels with 30 subjects and executed evaluation through e-mail. Recall and Precision were calculated by analyzing recommended programs from an E-mail questionnaire, and an evaluation of subjective satisfaction was conducted. As a result, we determined how much the result of an evaluation reflects viewer satisfaction by comparing the variation of subjects' satisfaction and the variation of objective evaluation criteria.