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2007
Springer

Using WordNet to Disambiguate Word Senses for Text Classification

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Using WordNet to Disambiguate Word Senses for Text Classification
In this paper, we propose an automatic text classification method based on word sense disambiguation. We use “hood” algorithm to remove the word ambiguity so that each word is replaced by its sense in the context. The nearest ancestors of the senses of all the non-stopwords in a give document are selected as the classes for the given document. We apply our algorithm to Brown Corpus. The effectiveness is evaluated by comparing the classification results with the classification results using manual disambiguation offered by Princeton University.
Ying Liu, Peter Scheuermann, Xingsen Li, Xingquan
Added 08 Jun 2010
Updated 08 Jun 2010
Type Conference
Year 2007
Where ICCS
Authors Ying Liu, Peter Scheuermann, Xingsen Li, Xingquan Zhu
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