Improving word sense disambiguation using topic features
This paper presents a novel approach for exploiting the global context for the task of word sense disambiguation (WSD). This is done by using topic features constructed using the latent dirichlet allocation (LDA) algorithm on unlabeled data. The features are incorporated into a modified näive Bayes...
Main Authors: | , , |
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Format: | Journal article |
Language: | English |
Published: |
2007
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