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Musical data mining for electronic music distribution

Research output: Contribution in Book/Report/ProceedingsConference contribution

Published

Publication date2001
Host publicationFirst International Conference on Web Delivering of Music, 2001. Proceedings.
EditorsP Nesi, P Bellini, C Busch
Place of publicationLOS ALAMITOS
PublisherIEEE COMPUTER SOC
Pages101-106
Number of pages6
ISBN (Print)0-7695-1284-4
Original languageEnglish

Abstract

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 titles of music in the world. In this paper we propose a method of classification based on musical data mining technique based on co-occurrence and correlation analysis that can be used for classification. It gives a new approach of 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 classifying titles of music in a kind of objective manner.