An Affective Music Recommendation System

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dc.contributor.authorPon, Auraeng
dc.contributor.authorSharlin, Ehudeng
dc.contributor.authorEagle, Davideng
dc.date.accessioned2010-12-22T18:17:08Z
dc.date.available2010-12-22T18:17:08Z
dc.date.issued2010-12-22T18:17:08Z
dc.description.abstractGiven that the affective features of music are often the most relevant criteria in selecting music, we propose in this abstract that a music database should be able to be categorized according to its affective influence, and likewise, music recommendations made with consideration to the user’s current affective state. This can be made possible using pre-existing emotion-measuring technology with new algorithms for selecting music with appropriate affective influence, as proven by several studies. An affective music recommender system could avoid many of the inadequacies of traditional recommender systems.eng
dc.description.refereedNoeng
dc.identifier.department2010-988-37eng
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/30999
dc.identifier.urihttp://hdl.handle.net/1880/48319
dc.language.isoengeng
dc.publisher.corporateUniversity of Calgaryeng
dc.publisher.facultyScienceeng
dc.subjectMusic recommendationeng
dc.subject.otherAffective computing, physiological measures, music affect, music categorizationeng
dc.titleAn Affective Music Recommendation Systemeng
dc.typetechnical reporteng
thesis.degree.disciplineComputer Scienceeng
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