A Personalized Music Filtering System Based on Melody Style Classification

  • Authors:
  • Fang-Fei Kuo;Man-Kwan Shan

  • Affiliations:
  • -;-

  • Venue:
  • ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
  • Year:
  • 2002

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Abstract

With the growth of digital music, the personalized musicfiltering system is helpful for users. Melody style is one ofthe music features to represent user's music preference. Inthis paper, we present a personalized content-based musicfiltering system to support music recommendation based onuser's preference of melody style. We propose the multitypemelody style classification approach to recommend themusic objects. The system learns the user preference bymining the melody patterns from the music access behaviorof the user. A two-way melody preference classifier istherefore constructed for each user. Music recommendationis made through this melody preference classifier.Performance evaluation shows that the filtering effect of theproposed approach meets user's preference.