Using multiple knowledge sources for word sense discrimination
Computational Linguistics
Retrieving collocations from text: Xtract
Computational Linguistics - Special issue on using large corpora: I
Corpus-based statistical sense resolution
HLT '93 Proceedings of the workshop on Human Language Technology
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This paper presents a method to resolve word sense ambiguity in a Korean-to-Japanese machine translation system using neural networks. The execution of our neural network model is based on the concept codes of a thesaurus. Most previous word sense disambiguation approaches based on neural networks have limitations due to their huge feature set size. By contrast, we reduce the number of features of the network to a practical size by using concept codes as features rather than the lexical words themselves.