Instance Based Learning with Automatic Feature Selection Applied to Word Sense Disambiguation

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This paper discusses instance based learning with automatic feature selection applied to word sense disambiguation.

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7 p.

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Mihalcea, Rada, 1974- August 2002.

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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 140 times . More information about this paper can be viewed below.

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Description

This paper discusses instance based learning with automatic feature selection applied to word sense disambiguation.

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7 p.

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Abstract: We describe an algorithm for Word Sense Disambiguation (WSD) that relies on a lazy learner improved with automatic feature selection. The algorithm was implemented in a system that achieves excellent performance on the set of data released during the SENSEVAL-2 competition. We present the results obtained and discuss the performance of various features in the context of supervised learning algorithms for WSD.

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  • Nineteenth International Conference on Computational Linguistics (COLING), 2002, Taipei, Taiwan

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  • August 2002

Added to The UNT Digital Library

  • Jan. 31, 2011, 2:01 p.m.

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  • March 27, 2014, 12:04 p.m.

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Mihalcea, Rada, 1974-. Instance Based Learning with Automatic Feature Selection Applied to Word Sense Disambiguation, paper, August 2002; (https://digital.library.unt.edu/ark:/67531/metadc30943/: accessed May 20, 2019), University of North Texas Libraries, Digital Library, https://digital.library.unt.edu; crediting UNT College of Engineering.