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A topological embedding of the lexicon for semantic distance computation

Published online by Cambridge University Press:  15 June 2010

N. DAVIS ,
C. GIRAUD-CARRIER  and
D. JENSEN
N. DAVIS
Affiliation:
Department of Computer Science, Brigham Young University, Provo, UT 84602, USA e-mail: cgc@cs.byu.edu
C. GIRAUD-CARRIER
Affiliation:
Department of Computer Science, Brigham Young University, Provo, UT 84602, USA e-mail: cgc@cs.byu.edu
D. JENSEN
Affiliation:
KJ Nova, Inc., Provo, UT 84601, USA
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Abstract

We show how a quantitative context may be established for what is essentially qualitative in nature by topologically embedding a lexicon (here, WordNet) in a complete metric space. This novel transformation establishes a natural connection between the order relation in the lexicon (e.g., hyponymy) and the notion of distance in the metric space, giving rise to effective word-level and document-level lexical semantic distance measures. We provide a formal account of the topological transformation and demonstrate the value of our metrics on several experiments involving information retrieval and document clustering tasks.

Type
Papers
Information
Natural Language Engineering , Volume 16 , Issue 3 , July 2010 , pp. 245 - 275
Copyright
Copyright © Cambridge University Press 2010

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