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http://dx.doi.org/10.9708/jksci/2012.17.11.133

A Tag-based Music Recommendation Using UniTag Ontology  

Kim, Hyon Hee (Dept. of Statistics and Information Science, Dongduk Women's University)
Publication Information
Journal of the Korea Society of Computer and Information / v.17, no.11, 2012 , pp. 133-140 More about this Journal
Abstract
In this paper, we propose a music recommendation method 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 algorithm is executed based on the profiles. To evaluate the proposed method, 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.
Keywords
Music recommendation; Tag ontology; Tag-based profile; Emotional tag;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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