Abstract
As the World Wide Web becomes a large source of digital music, the music recommendation system has got a great demand. There are several music recommendation systems for both commercial and academic areas, which deal with the user preference as fixed. However, since the music preferred by a user may change depending on the contexts, the conventional systems have inherent problems. This paper proposes a context-aware music recommendation system (CA-MRS) that exploits the fuzzy system, Bayesian networks and the utility theory in order to recommend appropriate music with respect to the context. We have analyzed the recommendation process and performed a subjective test to show the usefulness of the proposed system.
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© 2006 Springer-Verlag Berlin Heidelberg
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Park, HS., Yoo, JO., Cho, SB. (2006). A Context-Aware Music Recommendation System Using Fuzzy Bayesian Networks with Utility Theory. In: Wang, L., Jiao, L., Shi, G., Li, X., Liu, J. (eds) Fuzzy Systems and Knowledge Discovery. FSKD 2006. Lecture Notes in Computer Science(), vol 4223. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11881599_121
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DOI: https://doi.org/10.1007/11881599_121
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-45916-3
Online ISBN: 978-3-540-45917-0
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