Adjective Sense Disambiguation at the Border Between Unsupervised and Knowledge-Based Techniques

• Autorzy: Hristea F. , Popescu M.
• Języki publikacji: EN

Abstrakty

EN

The present paper extends a new word sense disambiguation method [9] to the case of adjectives. The method lies at the border between unsupervised and knowledge-based techniques. It performs unsupervised word sense disambiguation based on an underlying Näive Bayes model, while using WordNet as knowledge source for feature selection. The proposed extension of the disambiguation method makes ample use of the WordNet semantic relations that are typical of adjectives. Its performance is compared to that of previous approaches that rely on completely different feature sets. Test results show that feature selection using a knowledge source of type WordNet is more effective in the disambiguation of adjective senses than local type features (like part-of-speech tags) are.

Słowa kluczowe

EN

word sense disambiguation; unsupervised disambiguation; knowledge-based disambiguation; Bayesian classification; EM algorithm

• Wydawca: IOS Press
• Czasopismo: Fundamenta Informaticae
• Rocznik: 2009
• Tom: Vol. 91, nr 3-4
• Strony: 547--562
• Opis fizyczny: Bibliogr. 20 poz., tab.

Twórcy

autor

Hristea F.

autor

Popescu M.

• Department of Computer Science Faculty of Mathematics and Computer Science, University of Bucharest, Romania,

Bibliografia

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