Informetric analysis of a music database |
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Authors: | Nelson Michael Downie J Stephen |
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Affiliation: | (1) Faculty of Information and Media Studies, Middlesex College, Univ. of Western Ontario, London, Ontario, N6A 5B7, Canada;(2) Graduate School of Library and Information Science, University of Illinois at Urbana-Champaign, Champaign, (USA) |
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Abstract: | We analyse the statistical properties a database of musical notes for the purpose of designing an information retrieval system
as part of the Musifind project. In order to reduce the amount of musical information we convert the database to the intervals
between notes, which will make the database easier to search. We also investigate a further simplification by creating equivalence
classes of musical intervals which also increases the resilience of searches to errors in the query. The Zipf, Zipf-Mandelbrot,
Generalized Waring (GW) and Generalized Inverse Gaussian-Poisson (GIGP) distributions are tested against these various representations
with the GIGP distribution providing the best overall fit for the data. There are many similarities with text databases, especially
those with short bibliographic records. There are also some differences, particularly in the highest frequency intervals which
occur with a much lower frequency than the highest frequency “stopwords” in a text database. This provides evidence to support
the hypothesis that traditional text retrieval methods will work for a music database.
This revised version was published online in June 2006 with corrections to the Cover Date. |
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