Word sense disambiguation in a Korean-to-Japanese MT system using neural networks
Youjin Chung, Sin-Jae Kang, Kyonghi Moon, Jong-Hyeok Lee · 2002
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.