Presentation 2009-07-31
Artist Recommendation for Expanding Musical Preference
Yoshinobu SAKURAI, Ko FUJIMURA,
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Abstract(in English) We are developing an artist recommender system that increases diversity of musical preference since it will be effective for increasing sales. This paper proposes a new entropy-based measure that scores diversity of the music preference. We introduce this measure as an element of the benefit function that is to be maximized by the recommender system. This paper evaluated how the proposed measure reflects the diversity of musical preference by applying to a large number of playlists collected from the last.fm music community service. As the result, this measure increases according to the number of artists in user playlist and reflects diversity of preference when the number of artists is large.
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Keyword(in English) Recommender system / Artist recommendation / Preference diversity / last.fm
Paper # LOIS2009-17
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Conference Information
Committee LOIS
Conference Date 2009/7/23(1days)
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Registration To Life Intelligence and Office Information Systems (LOIS)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Artist Recommendation for Expanding Musical Preference
Sub Title (in English)
Keyword(1) Recommender system
Keyword(2) Artist recommendation
Keyword(3) Preference diversity
Keyword(4) last.fm
1st Author's Name Yoshinobu SAKURAI
1st Author's Affiliation Univercity of Electro-Communication()
2nd Author's Name Ko FUJIMURA
2nd Author's Affiliation Univercity of Electro-Communication:NTT Cyber Solutions Laboratories, NTT Corporation
Date 2009-07-31
Paper # LOIS2009-17
Volume (vol) vol.109
Number (no) 160
Page pp.pp.-
#Pages 6
Date of Issue