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Classification schemes for Internet resources revisited

Author: Diane Vizine-Goetz; OCLC. Office of Research.
Publisher: [Dublin, Ohio] : [OCLC Office of Research], [2002]
Edition/Format:   eBook : Document : English
Database:WorldCat
Summary:
Library classification schemes have become increasingly available in electronic form and undergone many enhancements that make them attractive for web knowledge organization. In fact, library professionals have been quite successful in applying library classification to Internet-based information services in a number of projects, both small and large. Yet, many opportunities remain for improving our general  Read more...
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Details

Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Diane Vizine-Goetz; OCLC. Office of Research.
OCLC Number: 53941739
Notes: Title from title screen (viewed Dec. 22, 2003).
Manuscript of paper published in Journal of Internet cataloguing 5(4) 2002, made available as a word document on the OCLC Office of Research website.
Details: Mode of access: Internet.
Other Titles: Journal of Internet cataloguing.
Responsibility: Diane Vizine-Goetz.

Abstract:

Library classification schemes have become increasingly available in electronic form and undergone many enhancements that make them attractive for web knowledge organization. In fact, library professionals have been quite successful in applying library classification to Internet-based information services in a number of projects, both small and large. Yet, many opportunities remain for improving our general knowledge organization tools and using them in new ways. In this article, the DDC hierarchy structure is compared to the subject trees of Internet directory services in terms categories, hierarchies, and distributions of postings. The schemes are also compared with respect to several general characteristics that support browsing. The findings suggest that the prospects are very good for developing effective DDC-based browsing structures to large collections.

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Linked Data


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