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Please use this identifier to cite or link to this item: http://hdl.handle.net/10119/5018

Title: An evidential reasoning approach to weighted combination of classifiers for word sense disambiguation
Authors: Le, Cuong Anh
Huynh, Van-Nam
Shimazu, Akira
Keywords: Computational linguistics
Weighted combination of classifiers
Word sense disambiguation
Dempster-Shafer theory of evidence
Issue Date: 2005
Publisher: Springer
Magazine name: Lecture Notes in Computer Science
Volume: 3587
Start page: 516
End page: 525
DOI: 10.1007/11510888_51
Abstract: Arguing that various ways of using context in word sense disambiguation (WSD) can be considered as distinct representations of a polysemous word, a theoretical framework for the weighted combination of soft decisions generated by experts employing these distinct representations is proposed in this paper. Essentially, this approach is based on the Dempster-Shafer theory of evidence. By taking the confidence of individual classifiers into account, a general rule of weighted combination for classifiers is formulated, and then two particular combination schemes are derived. These proposed strategies are experimentally tested on the datasets for four polysemous words, namely interest, line, serve, and hard, and obtained the better result in comparison with previous studies for all cases, with an exception of the word line.
Rights: This is the author-created version of Springer, Cuong Anh Le, Van-Nam Huynh and Akira Shimazu, Lecture Notes in Computer Science, 3587, 2005, 516-525. The original publication is available at www.springerlink.com, http://dx.doi.org/10.1007/11510888_51
URI: http://hdl.handle.net/10119/5018
Material Type: author
Appears in Collections:a10-1. 雑誌掲載論文 (Journal Articles)

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