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Experiments in automatic Library of Congress Classification

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  • Ray R. Larson

Abstract

This article presents the results of research into the automatic selection of Library of Congress Classification numbers based on the titles and subject headings in MARC records. The method used in this study was based on partial match retrieval techniques using various elements of new records (i.e., those to be classified) as “queries,” and a test database of classification clusters generated from previously classified MARC records. Sixty individual methods for automatic classification were tested on a set of 283 new records, using all combinations of four different partial match methods, five query types, and three representations of search terms. The results indicate that if the best method for a particular case can be determined, then up to 86% of the new records may be correctly classified. The single method with the best accuracy was able to select the correct classification for about 46% of the new records. © 1992 John Wiley & Sons, Inc.

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  • Ray R. Larson, 1992. "Experiments in automatic Library of Congress Classification," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 43(2), pages 130-148, March.
    • Handle: RePEc:bla:jamest:v:43:y:1992:i:2:p:130-148
    DOI: 10.1002/(SICI)1097-4571(199203)43:23.0.CO;2-S
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    Cited by:

    1. Charles-Antoine Julien & Pierre Tirilly & John E. Leide & Catherine Guastavino, 2012. "Constructing a true LCSH tree of a science and engineering collection," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(12), pages 2405-2418, December.

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