An evidential reasoning approach to weighted combination of classifiers for word sense disambiguation

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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. © Springer-Verlag Berlin Heidelberg 2005.

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APA

Le, C. A., Huynh, V. N., & Shimazu, A. (2005). An evidential reasoning approach to weighted combination of classifiers for word sense disambiguation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3587 LNAI, pp. 516–525). Springer Verlag. https://doi.org/10.1007/11510888_51

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