Interactive Music Recommendation System for Adapting Personal Affection: IMRAPA
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.
KeywordsMusic retrieval system Interactive system Affection Personalization
- 1.Bogdanov, D., Herrera, P.: How much metadata do we need in music recommendation? a subjective evaluation using preference sets. In: Proceedings of 2011 International Society for Music Information Retrieval Conference, pp. 97–102 (2011)Google Scholar
- 2.Flexer, A., Gasser, M., Schnitzer, D.: Limitations of interactive music recommendation based on audio content. In: Proceedings of the 5th Audio Mostly Conference: A Conference on Interaction with Sound, pp. 96–102 (2010)Google Scholar
- 3.Knees, P., Pohle, T., Schedl, M., Seyerlehner, D.S.K., Widmer, G.: Augmenting text-based music retrieval with audio similarity. In: Proceedings of 10th International Society for Music Information Retrieval Conference, pp. 579–584 (2009)Google Scholar
- 4.Langley, P., Iba, W., Thompson, K.: An analysis of bayesian classifiers. In: Proceedings of the 10th National Conference on Artical Intelligence, pp. 223–228 (1992)Google Scholar
- 5.Yamanishi, R., Ito, Y., Kato, S.: Relationships between emotional evaluation of music and acoustic fluctuation properties. In: Proceedings of IEEE Symposium on Computers & Informatics, pp. 721–726 (2011)Google Scholar