Word Sense Disambiguation based on Semantic Density

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This article discusses word sense disambiguation based on semantic density.

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7 p.

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Mihalcea, Rada, 1974- & Moldovan, Dan I. August 1998.

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This article discusses word sense disambiguation based on semantic density.

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7 p.

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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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  • 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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  • August 1998

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  • April 13, 2012, 9:48 a.m.

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  • March 27, 2014, 1:37 p.m.

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Mihalcea, Rada, 1974- & Moldovan, Dan I. Word Sense Disambiguation based on Semantic Density, paper, August 1998; (digital.library.unt.edu/ark:/67531/metadc83303/: accessed August 18, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT College of Engineering.