A context-aware music recommendation system using fuzzy bayesian networks with utility theory

  • Authors:
  • Han-Saem Park;Ji-Oh Yoo;Sung-Bae Cho

  • Affiliations:
  • Department of Computer Science, Yonsei University, Seoul, Korea;Department of Computer Science, Yonsei University, Seoul, Korea;Department of Computer Science, Yonsei University, Seoul, Korea

  • Venue:
  • FSKD'06 Proceedings of the Third international conference on Fuzzy Systems and Knowledge Discovery
  • Year:
  • 2006

Quantified Score

Hi-index 0.00

Visualization

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.