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dc.contributor.authorShan, Man-Kwanen_US
dc.contributor.authorKuo, Fang-Feien_US
dc.contributor.authorChiang, Meng-Fenen_US
dc.contributor.authorLee, Suh-Yinen_US
dc.date.accessioned2014-12-08T15:12:58Z-
dc.date.available2014-12-08T15:12:58Z-
dc.date.issued2009-05-01en_US
dc.identifier.issn0957-4174en_US
dc.identifier.urihttp://dx.doi.org/10.1016/j.eswa.2008.09.042en_US
dc.identifier.urihttp://hdl.handle.net/11536/10010-
dc.description.abstractWith the growth of digital music, the development of music recommendation is helpful for users to pick desirable music pieces from a huge repository of music. The existing music recommendation approaches are based on a user's preference on music. However, sometimes, it might better meet users' requirement to recommend music pieces according to emotions. In this paper, we propose a novel framework for emotion-based music recommendation. The core of the recommendation framework is the construction of the music emotion model by affinity discovery from film music, which plays an important role in conveying emotions in film. We investigate the music feature extraction and propose the Music Affinity Graph and Music Affinity Graph-Plus algorithms for the construction of music emotion model. Experimental result shows the proposed emotion-based music recommendation achieves 85% accuracy in average. (C) 2008 Elsevier Ltd. All rights reserved.en_US
dc.language.isoen_USen_US
dc.subjectMusic recommendationen_US
dc.subjectEmotion detectionen_US
dc.subjectAffinity discoveryen_US
dc.titleEmotion-based music recommendation by affinity discovery from film musicen_US
dc.typeArticleen_US
dc.identifier.doi10.1016/j.eswa.2008.09.042en_US
dc.identifier.journalEXPERT SYSTEMS WITH APPLICATIONSen_US
dc.citation.volume36en_US
dc.citation.issue4en_US
dc.citation.spage7666en_US
dc.citation.epage7674en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000264528600042-
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