Most previous word sense disambiguation approaches based on neural networks were impractical due to their huge feature set size. We propose a method for resolving word sense ambiguity using neural networks with refined concept co-occurrence information (CCI) as features. Using CCI refinement processing, we reduce the number of features of the network to a practical size. We also show that word sense disambiguation can be improved by combining several clues rather than using them independently.

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... ur method is fully automated and does not require any hand coding of large-scale resources.