Presentation 2004/10/11
Recommendation Algorithm based on Bayesian Network
Chihiro Ono, Yoichi Motomura, Hideki Asoh,
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Abstract(in English) Recently, recommendation algorithm and services has been studied, which provide appropriate contents or items from a large amount of available contents or services based on personal and contents profiles. So far, content-based filtering and collaborative filtering have widely been used as a recommendation algorithm. They, however, have problems such as unsuitable formalization of human perception and preferences based on content analysis, and extreme sparsity of available data as users typically rate only very few contents. We are now studying a recommendation system based on Bayesian network to solve these issues. In this paper, we first describe requirements for recommendation, then describe model definition policy and an example model based on the results of the questionnaire about movie preference taken from 1600 users.
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Keyword(in English) Bayesian Network / Recommendation
Paper # NC2004-66
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Committee NC
Conference Date 2004/10/11(1days)
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Registration To Neurocomputing (NC)
Language JPN
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Title (in English) Recommendation Algorithm based on Bayesian Network
Sub Title (in English)
Keyword(1) Bayesian Network
Keyword(2) Recommendation
1st Author's Name Chihiro Ono
1st Author's Affiliation KDDI R&D Laboratories, Inc()
2nd Author's Name Yoichi Motomura
2nd Author's Affiliation Digital Human Research Center, National Institute of Advanced Industrial Science and Technology
3rd Author's Name Hideki Asoh
3rd Author's Affiliation Information Technology Research Institute, National Institute of Advanced Industrial Science and Technology
Date 2004/10/11
Paper # NC2004-66
Volume (vol) vol.104
Number (no) 348
Page pp.pp.-
#Pages 6
Date of Issue