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Interactive music recommendation system for adapting personal affection: IMRAPA

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2012) 7522 LNCS 417-420
DOI: 10.1007/978-3-642-33542-6_42
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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. © 2012 Springer-Verlag Berlin Heidelberg.

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APA

Tada, K., Yamanishi, R., & Kato, S. (2012). Interactive music recommendation system for adapting personal affection: IMRAPA. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7522 LNCS, pp. 417–420). https://doi.org/10.1007/978-3-642-33542-6_42

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