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Hybrid Music Filtering for Recommendation Based Ubiquitous Computing Environment

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Rough Sets and Current Trends in Computing (RSCTC 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4259))

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Abstract

Existing studies on music recommendation systems pose the problem of being incapable of proposing proper recommendations according to user conditions due to limited metadata obtained from users using a content-based filtering method. Although some studies have been conducted in recent years on recommendation systems employing a great amount of environmental information, they have been unable to satisfy information requested by the user. Thus, this study defines context information required to select music and proposes a hybrid filtering method that exploits a content-based filtering and collaborative filtering method in ubiquitous environments. In addition, this study developed a music recommendation system based on these filtering methods which significantly improved user satisfaction for music selection.

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© 2006 Springer-Verlag Berlin Heidelberg

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Kim, JH., Jung, KY., Lee, JH. (2006). Hybrid Music Filtering for Recommendation Based Ubiquitous Computing Environment. In: Greco, S., et al. Rough Sets and Current Trends in Computing. RSCTC 2006. Lecture Notes in Computer Science(), vol 4259. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11908029_82

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  • DOI: https://doi.org/10.1007/11908029_82

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-47693-1

  • Online ISBN: 978-3-540-49842-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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