Automatic indexing and generation of classification systems by algorithm

Hoyle, W.G.

doi:10.1016/0020-0271(73)90091-0

Cited by 11 publications

(1 citation statement)

References 7 publications

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“…Early work by Maron (1961) and Borko andBernick (1962, 1963) concentrated on automatically assigning documents to broad predefined classes based on terms used in the abstract of the document. Later examples of automatic classification using predefined classes may be found in Hoyle (1973) and Kar and White (1978). However, much of the work on automatic classification carried out in the 1970s and 1980s was concerned with clustering or grouping documents based on similarities between their content, without reference to predefined classes.…”

Section: Introductionmentioning

confidence: 99%

Experiments in automatic Library of Congress Classification

Larson

1992

J. Am. Soc. Inf. Sci.

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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 88% 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.

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