A Semi-Complete Disambiguation Algorithm for Open Text

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This paper discusses a semi-complete disambiguation algorithm for open text.

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1 p.

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Mihalcea, Rada, 1974- 2000.

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This paper is part of the collection entitled: UNT Scholarly Works and was provided by UNT College of Engineering to Digital Library, a digital repository hosted by the UNT Libraries. It has been viewed 75 times . More information about this paper can be viewed below.

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This paper discusses a semi-complete disambiguation algorithm for open text.

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1 p.

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Copyright 2000 American Association for Artificial Intelligence (AAAI). All rights reserved. http://www.aaai.org

Abstract: Word Sense Disambiguation (WSD) is one of the most difficult areas of Natural Language Processing (NLP); the semantic comprehension of a text, and the possibility to expand a text with semantically related information, drastically depends on the availability of a highly accurate WSD algorithm. Solutions considered so far by researchers for the WSD problem, are making use of machine readable dictionaries (Leacock, Chodorow and Miller 1998), or the information gathered from raw or semantically disambiguated corpora (Yarowsky 1995). These methods are designed either to work with a few pre-selected words, in which case a high accuracy is obtained, or they are general methods which disambiguate, with lower precision, all the words in a text. With the present work, the authors are trying to achieve a compromise between these two different directions. There are fields in NLP, like Information Retrieval and others, which could benefit from a method which performs a semi-complete disambiguation (i.e. it disambiguates only a certain percentage of the words in a text), but which is highly accurate.

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  • Seventeenth National Conference on Artificial Intelligence, 2000, Austin, Texas, United States

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  • 2000

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  • April 13, 2012, 9:48 a.m.

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  • March 27, 2014, 1:05 p.m.

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Mihalcea, Rada, 1974-. A Semi-Complete Disambiguation Algorithm for Open Text, paper, 2000; (digital.library.unt.edu/ark:/67531/metadc83293/: accessed December 11, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT College of Engineering.