Experiments on word sense disambiguation using several machine-learning methods

摘要

In this research, we carried out experiments on Japanese word sense disambiguation in the RWC corpus by using the four machine-learning methods: the support-vector machine method, the maximum-entropy model method, the decision-list method, the simple Bayes method. The result was that the support-vector machine method produced the best precisions among them.