Determining the specificity of terms using inside-outside information: a necessary condition of term hierarchy mining

This paper introduces new specificity measuring methods of terms using inside and outside information. Specificity of a term is the quantity of domain specific information contained in the term. Specific terms have a larger quantity of domain information than general terms. Specificity is an important necessary condition for building hierarchical relations among terms. If t(1) is a hyponym of t(2) in a domain term hierarchy, then the specificity of t(1) is greater than that of t(2). As domain specific terms are commonly compounds of the generic level term and some modifiers, inside information is important to represent the meaning of terms. Outside contextual information is also used to complement the shortcomings of inside information. We propose an information theoretic method to measure the quantity of terms. Experiments showed promising results with a precision of 73.9% when applied to terms in the MeSH thesaurus. (c) 2006 Published by Elsevier B.V.
Publisher
ELSEVIER SCIENCE BV
Issue Date
2006-10
Language
ENG
Description

Received 15 November 2004; received in revised form 13 November 2005; accepted 30 November 2005 Available online 11 July 2006

Citation

INFORMATION PROCESSING LETTERS, v.100, no.2, pp.76 - 82

ISSN
0020-0190
DOI
10.1016/j.ipl.2005.11.024
URI
http://hdl.handle.net/10203/3583
Appears in Collection
CS-Journal Papers(저널논문)
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