By Topic

Musical data mining for electronic music distribution

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Pachet, F. ; Sony CSL-Paris, Paris, France ; Westermann, G. ; Laigre, D.

Music classification is a key ingredient for electronic music distribution. Because of the lack of standards in music classification (or the lack of enforcement of existing standards), there is a huge amount of unclassified music titles in the world. The authors propose a classification method based on a musical data mining technique based on co-occurrence and correlation analysis that can be used for classification. It gives a new approach to similarity between several titles of music or several artists. We study large corpora of textual information referring titles of music or artists whose names are decided by humans without particular constraints other than readability, and draw various hypotheses concerning the natural similarities that emerge from these corpora. Based on a clustering technique, we show that interesting groups can reveal specific music genres and allow classification of music titles in an objective manner.

Published in:

Web Delivering of Music, 2001. Proceedings. First International Conference on

Date of Conference:

23-24 Nov. 2001