A Simple Approach to Building Ensembles of Naive Bayesian Classifiers for Word Sense Disambiguation

Computer Science – Computation and Language

Scientific paper

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7 pages, Latex, uses colnaacl.sty. Appears in Proceedings of NAACL, pages 63-69, May 2000, Seattle, WA

Scientific paper

This paper presents a corpus-based approach to word sense disambiguation that builds an ensemble of Naive Bayesian classifiers, each of which is based on lexical features that represent co--occurring words in varying sized windows of context. Despite the simplicity of this approach, empirical results disambiguating the widely studied nouns line and interest show that such an ensemble achieves accuracy rivaling the best previously published results.

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