Content-based filtering system for music data
Kazuhiro Iwahama, Yasuto Hijikata, S. Nishida · 2004
Recommender systems, which recommend appropriate information to users from enormous amount of information, are becoming popular. There are two methods to realize recommender systems. One is content-based filtering, and the other is collaborative filtering. Many systems using the former method deal with text data, and few systems deal with music data. This paper proposes a content-based filtering system that targets music data in MIDI format. First, we analyze characteristics of feature parameters about music data in MIDI format. Then we propose a filtering method based on the above feature parameters. Finally, we build a prototype system with standard technology of the Internet.