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dc.contributor.authorWiyartanti, L.-
dc.contributor.authorKim, L.-
dc.date.accessioned2024-01-12T07:22:56Z-
dc.date.available2024-01-12T07:22:56Z-
dc.date.created2022-03-07-
dc.date.issued2009-11-
dc.identifier.issn0000-0000-
dc.identifier.urihttps://pubs.kist.re.kr/handle/201004/80898-
dc.description.abstractMusic information retrieval had become an interesting research subject to be explored. The development of information clustering leads the user to find related contents and interests more easily. In this paper, we present a recommendation of similar music artists based on the music genre classification, artist's era, and social rating information. The algorithm is performed in three steps: compute similarity measure on music genre; apply the user rating factor to the artist; and finalize the similarity by selecting artists who have the same period of music activities. The Jaccard coefficient and Nearest-Neighbor search have been used in the computation. The experiment shows that we can obtain better results using the proposed method. ? 2009 IADIS.-
dc.languageEnglish-
dc.publisherIADIS-
dc.titleFinding similar music artists for recommendation-
dc.typeConference-
dc.description.journalClass1-
dc.identifier.bibliographicCitationIADIS International Conference WWW/Internet 2009, ICWI 2009, pp.535 - 542-
dc.citation.titleIADIS International Conference WWW/Internet 2009, ICWI 2009-
dc.citation.startPage535-
dc.citation.endPage542-
dc.citation.conferencePlaceIT-
dc.citation.conferencePlaceRome-
dc.citation.conferenceDate2009-11-19-
dc.relation.isPartOfProceedings of the IADIS International Conference WWW/Internet 2009, ICWI 2009-
dc.identifier.scopusid2-s2.0-84946546673-
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KIST Conference Paper > 2009
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