Presentation 2003/5/26
Collaborative Filtering Based on User's Hidden Preference Model : Extraction User's Preference from User's Rating
noriaki kawamae,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) This paper proposes a novel method in collaborative filtering, which helps users in getting contents and items. The effectiveness of collaborative filtering can be assessed by its accuracy of prediction, and the accuracy of prediction depends on the way to seek similar users in preference. Previous works seek these users by the similarity between the users' rating. But our method measures the similarity by the users' preference. To extract these users' preference, we propose the weighting method for item and the introduction of users' hidden preference model. Besides these, we define the formula to predict users' rating. Through the experiments, we can confirm the effectiveness of our method in the accuracy of prediction.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Collaborative Filtering / Knowledge Sharing / User's Hidden Preference / Factor Analysis / History Analysis
Paper # DE2003-5
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Committee DE
Conference Date 2003/5/26(1days)
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Paper Information
Registration To Data Engineering (DE)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Collaborative Filtering Based on User's Hidden Preference Model : Extraction User's Preference from User's Rating
Sub Title (in English)
Keyword(1) Collaborative Filtering
Keyword(2) Knowledge Sharing
Keyword(3) User's Hidden Preference
Keyword(4) Factor Analysis
Keyword(5) History Analysis
1st Author's Name noriaki kawamae
1st Author's Affiliation NTT Information Sharing Platform Laboratories()
Date 2003/5/26
Paper # DE2003-5
Volume (vol) vol.103
Number (no) 104
Page pp.pp.-
#Pages 6
Date of Issue