Predicting Library of Congress classifications from Library of Congress subject headings
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چکیده
منابع مشابه
Predicting Library of Congress classifications from Library of Congress subject headings
This paper addresses the problem of automatically assigning a Library of Congress Classification (LCC) to a work given its set of Library of Congress Subject Headings (LCSH). LCCs are organized in a tree: The root node of this hierarchy comprises all possible topics, and leaf nodes correspond to the most specialized topic areas defined. We describe a procedure that, given a resource identified ...
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This paper addresses the problem of automatically assigning a Library of Congress Classification (LCC) to a work given its set of Library of Congress Subject Headings (LCSH). LCC are organized in a tree: the root node of this hierarchy comprises all possible topics, and leaf nodes correspond to the most specialized topic areas defined. We describe a procedure that, given a resource identified b...
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This paper will explore using XSLT stylesheets to translate LCSH Authority Records from MARC/XML or MADS XML formats into RDF documents according to the SKOS project's Quick Guide to Publishing a Thesaurus on the Semantic Web. Creating an RDF Data Store that represents the content of LCSH will have tremendous long-term benefits in allowing a greater breadth of applications to make full use of t...
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Social tagging, as a recent approach for creating metadata, has caught the attention of library and information science researchers. Many researchers recommend incorporating social tagging into the library environment and combining folksonomies with formal classification. However, some researchers are concerned with the quality issues of social annotation because of its uncontrolled nature. In ...
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ژورنال
عنوان ژورنال: Journal of the American Society for Information Science and Technology
سال: 2004
ISSN: 1532-2882,1532-2890
DOI: 10.1002/asi.10360