Presentation 2010-02-16
A note on music recommendation based on personal preferences : Introduction of similarity index for preference model
Kazuya KOBAYASHI, Miki HASEYAMA,
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Abstract(in English) This paper proposes a new music recommendation method based on preference similarity between users. In the proposed method, by applying Support Vector Data Description(SVDD)to musical feature vectors which are calculated from training data, we calculate hyperspheres discriminating preferred music pieces. Furthermore, we newly define a degree of preference similarity between users by using the hyperspheres, and make the combination of similar users in preference based on this degree. Finally, recommended music pieces are outputted based on two probabilities calculated by each center of the hypersphere for the pair of users. Therefore, based on the preference similarity between users, recommendation of music pieces can be effectively realized.
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Keyword(in English) Music recommendation / SVDD / Musical feature
Paper # ITS2009-67,IE2009-161
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Committee ITS
Conference Date 2010/2/8(1days)
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Paper Information
Registration To Intelligent Transport Systems Technology (ITS)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A note on music recommendation based on personal preferences : Introduction of similarity index for preference model
Sub Title (in English)
Keyword(1) Music recommendation
Keyword(2) SVDD
Keyword(3) Musical feature
1st Author's Name Kazuya KOBAYASHI
1st Author's Affiliation Graduate School of Information Science and Technology, Hokkaido University()
2nd Author's Name Miki HASEYAMA
2nd Author's Affiliation Graduate School of Information Science and Technology, Hokkaido University
Date 2010-02-16
Paper # ITS2009-67,IE2009-161
Volume (vol) vol.109
Number (no) 414
Page pp.pp.-
#Pages 4
Date of Issue