Music clustering with constraints

Wei Peng, Tao Li, Mitsunori Ogihara

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Scopus citations

Abstract

This paper studies the problem of building clusters of music tracks in a collection of popular music in the presence of constraints. The constraints come naturally in the context of music applications. For example, constraints can be generated from the background knowledge (e.g., two artists share similar styles) and the user access patterns (e.g., two pieces of music share similar access patterns across multiple users). We present an approach based on the generalized constraint clustering algorithm by incorporating the constraints for grouping music by "similar" artists. The approach is evaluated on a data set consisting of 53 albums covering 41 popular artists. The "correctness" of the clusters generated is tested using artist similarity provided by All Music Guide.

Original languageEnglish (US)
Title of host publicationProceedings of the 8th International Conference on Music Information Retrieval, ISMIR 2007
Pages27-32
Number of pages6
StatePublished - Dec 1 2007
Externally publishedYes
Event8th International Conference on Music Information Retrieval, ISMIR 2007 - Vienna, Austria
Duration: Sep 23 2007Sep 27 2007

Publication series

NameProceedings of the 8th International Conference on Music Information Retrieval, ISMIR 2007

Other

Other8th International Conference on Music Information Retrieval, ISMIR 2007
CountryAustria
CityVienna
Period9/23/079/27/07

ASJC Scopus subject areas

  • Music
  • Information Systems

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  • Cite this

    Peng, W., Li, T., & Ogihara, M. (2007). Music clustering with constraints. In Proceedings of the 8th International Conference on Music Information Retrieval, ISMIR 2007 (pp. 27-32). (Proceedings of the 8th International Conference on Music Information Retrieval, ISMIR 2007).