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

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.

• Publication year

  2000

• Venue

  Applied Natural Language Processing Conference

• Publication date

  2000-04-29

• Fields of study

  Linguistics, Computer Science

• Identifiers
  arXiv cs/0005006
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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