A Context-Aware Music Recommendation System Using Fuzzy Bayesian Networks with Utility Theory

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.

• Type: Conference
• Year: 2006
• Where: FSKD
• Authors: Han-Saem Park, Ji-Oh Yoo, Sung-Bae Cho
• Keywords: FSKD 2006, Fuzzy Logic, Music Recommendation, Music Recommendation Systems, Recommendation System