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ABSTRACT

Two approaches to distributing music on the Net---the hard way and the easy way---compete and complement each other in the quest for meaningful musical metadata.

REFERENCES

• 1: Allamanche, E., Herre, J., Helmuth, O., Frba, B., Kasten, T., and Cremer, M. Content-based identification of audio material using MPEG-7 low-level description. In Proceedings of the International Symposium of Music Information Retrieval (2001).
• 2: Aucouturier, J. and Pachet, F. Representing musical genre: A state of the art. Journal of New Music Research 32, 1 (Jan. 2003).
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• 4: William W. Cohen , Wei Fan, Web-collaborative filtering: recommending music by crawling the Web, Proceedings of the 9th international World Wide Web conference on Computer networks : the international journal of computer and telecommunications netowrking, p.685-698, June 2000, Amsterdam, The Netherlands
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• 6: Lepain, P. Polyphonic pitch extraction from musical signals. Journal of New Music Research 28, 4 (Apr. 1999).
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• 8: F. Pachet , G. Westermann , D. Laigre, Musical Data Mining for Electronic Music Distribution, Proceedings of the First International Conference on WEB Delivering of Music (WEDELMUSIC'01), p.101, November 23-24, 2001
• 9: Philippe, P. Low-level musical descriptors for MPEG-7. Signal Processing: Image Communication 16 (2000).
• 10: Upendra Shardanand , Pattie Maes, Social information filtering: algorithms for automating “word of mouth”, Proceedings of the SIGCHI conference on Human factors in computing systems, p.210-217, May 07-11, 1995, Denver, Colorado, United States [doi>10.1145/223904.223931]
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INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval

Additional Classification:
  H. Information Systems
  H.2 DATABASE MANAGEMENT
      H.2.7 Database Administration

  K. Computing Milieux
  K.6 MANAGEMENT OF COMPUTING AND INFORMATION SYSTEMS