Experiments in automatic Library of Congress Classification

Ray R. Larson

Journal of the American Society for Information Science, 1992, vol. 43, issue 2, 130-148

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.

Date: 1992
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://doi.org/10.1002/(SICI)1097-4571(199203)43:23.0.CO;2-S

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:jamest:v:43:y:1992:i:2:p:130-148

Ordering information: This journal article can be ordered from
https://doi.org/10.1002/(ISSN)1097-4571

Access Statistics for this article

More articles in Journal of the American Society for Information Science from Association for Information Science & Technology
Bibliographic data for series maintained by Wiley Content Delivery ().