Content-Based Filtering System for Music Data

Authors:
Kazuhiro Iwahama;Yoshinori Hijikata;Shogo Nishida
Affiliations:
-;-;-
Venue:
SAINT-W '04 Proceedings of the 2004 Symposium on Applications and the Internet-Workshops (SAINT 2004 Workshops)
Year:
2004

Citing 4
Cited 3

Information filtering

Communications of the ACM - Special issue on information filtering
C4.5: programs for machine learning

C4.5: programs for machine learning
Recommender systems

Communications of the ACM
A music recommendation system based on music data grouping and user interests

Proceedings of the tenth international conference on Information and knowledge management

Using Evolving Agents to Critique Subjective Music Compositions

Computational Intelligence and Security
Evaluating subjective compositions by the cooperation between human and adaptive agents

MICAI'06 Proceedings of the 5th Mexican international conference on Artificial Intelligence
A web service recommendation system based on users' reputations

PRIMA'11 Proceedings of the 14th international conference on Agents in Principle, Agents in Practice

Quantified Score

Hi-index	0.00

Visualization

Abstract

Recommender systems, which recommend appropriate information to users from enormous amount of information, are becoming popular. There are two methods to realize recommendersystems. One is content-based .ltering, and the other is collaborative .ltering. 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, weanalyze 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.