Word sense disambiguation for free-text indexing using a massive semantic network
CIKM '93 Proceedings of the second international conference on Information and knowledge management
SIGDOC '86 Proceedings of the 5th annual international conference on Systems documentation
Lexical cohesion computed by thesaural relations as an indicator of the structure of text
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Introduction to the special issue on word sense disambiguation: the state of the art
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Word-sense disambiguation using statistical models of Roget's categories trained on large corpora
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HLT '93 Proceedings of the workshop on Human Language Technology
Measuring semantic similarity in the taxonomy of WordNet
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AusDM '08 Proceedings of the 7th Australasian Data Mining Conference - Volume 87
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This paper designs a novel lexical hub to disambiguate word sense, using both syntagmatic and paradigmatic relations of words. It only employs the semantic network of WordNet to calculate word similarity, and the Edinburgh Association Thesaurus (EAT) to transform contextual space for computing syntagmatic and other domain relations with the target word. Without any back-off policy the result on the English lexical sample of SENSEVAL-21 shows that lexical cohesion based on edge-counting techniques is a good way of unsupervisedly disambiguating senses.