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Interactive Music Recommendation System for Adapting Personal Affection: IMRAPA

  • Keigo Tada
  • Ryosuke Yamanishi
  • Shohei Kato
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7522)

Abstract

We have so various types of entertainment, and music is one of the most popular one. In this paper, we proposed music recommendation system that interactively adapts a user’s personal affection with only a simple operation, in which both acoustic and meta features are used. The more a user uses the proposed system, the better the system adapts the user’s personal affection and recommends the suitable songs. Through the evaluational experiment, we confirmed that the proposed system could recommend songs adapting user’s personal affection even if the personal affection variated.

Keywords

Music retrieval system Interactive system Affection Personalization 

References

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Copyright information

© IFIP International Federation for Information Processing 2012

Authors and Affiliations

  • Keigo Tada
    • 1
  • Ryosuke Yamanishi
    • 2
  • Shohei Kato
    • 1
  1. 1.Dept. of Computer Science and Engineering, Graduate School of EngineeringNagoya Institute of TechnologyShowa-kuJapan
  2. 2.Dept. of Media TechnologyRitsumeikan UniversityKusatsuJapan

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