Hybrid music filtering for recommendation based ubiquitous computing environment

Authors:
Jong-Hun Kim;Kyung-Yong Jung;Jung-Hyun Lee
Affiliations:
Department of Computer Science, Engineering Inha University, Incheon, Korea;School of Computer Information Engineering, Sangji University, Korea;Department of Computer Science, Engineering Inha University, Incheon, Korea
Venue:
RSCTC'06 Proceedings of the 5th international conference on Rough Sets and Current Trends in Computing
Year:
2006

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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.