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Feasibility of a computer-generated subject validation file based on frequency of occurrence of assigned LC subject headings

Author: Lois Mai Chan; Diane Vizine-Goetz
Publisher: [Dublin, Ohio] : [OCLC], [1996]
Edition/Format:   Book : Document   Computer File : English
Database:WorldCat
Summary:
The library community has long recognized the need for, and potential usefulness of, a subject heading validation file. This project explores the feasibility of automatically creating such a file through scans of the Online Union Catalog (OLUC), given certain restraints. First, the file would not be exhaustive, but would instead contain the majority of the most used headings. Second, the predicted level of errors in  Read more...
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Details

Material Type: Document, Internet resource
Document Type: Book, Computer File, Internet Resource
All Authors / Contributors: Lois Mai Chan; Diane Vizine-Goetz
OCLC Number: 54424062
Notes: Article available via OCLC's Digital Archive.
Title from title screen (viewed February 15, 2004).
IN: Authority control in the 21st century: an invitational conference, March 31-April 1, 1996, proceedings. Reprinted from Annual review of OCLC research 1995.
Details: Mode of access: Internet.
Other Titles: Annual review of OCLC research, 1995.
Authority control in the 21st century : an invitational conference, March 31-April 1, 1996 : proceedings.
Responsibility: Lois Mai Chan and Diane Vizine-Goetz.

Abstract:

The library community has long recognized the need for, and potential usefulness of, a subject heading validation file. This project explores the feasibility of automatically creating such a file through scans of the Online Union Catalog (OLUC), given certain restraints. First, the file would not be exhaustive, but would instead contain the majority of the most used headings. Second, the predicted level of errors in the file should be low. Thus, the project focuses on finding the density and distribution of assigned headings, and the relationship, if it exists, between density and error rate.

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Linked Data


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