Word Sense Disambiguation based on Semantic Density

Description:

This article discusses word sense disambiguation based on semantic density.

Creator(s):
Creation Date: August 1998
Partner(s):
UNT College of Engineering
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UNT Scholarly Works
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Creator (Author):
Mihalcea, Rada, 1974-

University of North Texas; Southern Methodist University

Creator (Author):
Moldovan, Dan I.

Southern Methodist University

Date(s):
  • Creation: August 1998
Description:

This article discusses word sense disambiguation based on semantic density.

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Abstract: This paper presents a Word Sense Disambiguation method based on the idea of semantic density between words. The disambiguation is done in the context of WordNet. The Internet is used as a raw corpora to provide statistical information for word associations. A metric is introduced and used to measure the semantic density and to rank all possible combinations of the senses of two words. This method provides a precision of 58% in indicating the correct sense for both words at the same time. The precision increases as we consider more choices: 70% for top two ranked and 73% for top three ranked.

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7 p.

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Keyword(s): word sense disambiguation | natural language processing | WordNet
Source: Thirty-Sixth Annual Meeting of the Association for Computational Linguistics and 17th International Conference on Computational Linguistics ( COLING-ACL) Workshop, 1998, Montreal, Quebec, Canada
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Partner:
UNT College of Engineering
Collection:
UNT Scholarly Works
Identifier:
  • ARK: ark:/67531/metadc83303
Resource Type: Paper
Format: Text
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Access: Public