Presentation 2005-07-14
OWL Representation of Personal Music Preference Data and The Application to Music Information Recommendation
Yuichi Takeuchi, Masaki Aono,
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Abstract(in English) With the rapid spread of the Internet, more and more massive dataset is available on-line. However, it is difficult to acquire a valuable piece of information that a person really wants. Information filtering has been one of the techniques that extract important pieces of information for individuals. Among many information filtering techniques, we will focus on the recommender system for an individual by taking music data as an example. In this paper, we will propose a new method for recommending songs by using a personalized data structure with an OWL, Web Ontology Language, that reflects person's preference, and by introducing a similarity measure, which we call "OWL structural similarity", between two OWLs. We also present preliminary experimental results including the comparison between collaborative filtering, Jaccard coefficient-based method, and proposed OWL structural similarity-based method.
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Keyword(in English) OWL / ontology / information recommendation / similarity
Paper # DE2005-66
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Committee DE
Conference Date 2005/7/7(1days)
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Registration To Data Engineering (DE)
Language JPN
Title (in Japanese) (See Japanese page)
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Title (in English) OWL Representation of Personal Music Preference Data and The Application to Music Information Recommendation
Sub Title (in English)
Keyword(1) OWL
Keyword(2) ontology
Keyword(3) information recommendation
Keyword(4) similarity
1st Author's Name Yuichi Takeuchi
1st Author's Affiliation Toyohashi University of Technology()
2nd Author's Name Masaki Aono
2nd Author's Affiliation Toyohashi University of Technology
Date 2005-07-14
Paper # DE2005-66
Volume (vol) vol.105
Number (no) 172
Page pp.pp.-
#Pages 5
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