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A Tag-based Music Recommendation Using UniTag Ontology

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2012, 17(11), pp.133-140
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science

Hyon Hee Kim 1

1동덕여자대학교

Accredited

ABSTRACT

In this paper, we propose amusic recommendationmethod considering users’ tags by collaborative tagging in a social music site. Since collaborative tagging allows a user to add keywords chosen by himself to web resources, it provides users' preference about the web resources concretely. In particular, emotional tags which represent human’s emotion contain users’ musical preference more directly than factual tags which represent facts such as musical genre and artists. Therefore, to classify the tags into the emotional tags and the factual tags and to assign weighted values to the emotional tags, a tag ontology called UniTag is developed. After preprocessing the tags, the weighted tags are used to create user profiles, and the music recommendation algorithmis executed based on the profiles. To evaluate the proposedmethod, a conventional playcount-based recommendation, an unweighted tag-based recommendation, and an weighted tag-based recommendation are executed. Our experimental results show that the weighted tag-based recommendation outperforms other two approaches in terms of precision.

Citation status

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