A Vicarious Words Method for Word Sense Discrimination

This paper presents a new approach based on Vicarious Words (VWs) to resolve Word Sense Discrimination (WSD) in Chinese language. VWs are particular artificial ambiguous words, which can be used to realize unsupervised WSD. A Bayesian classifier is implemented to test the efficacy of the VW solution on Senseval-3 Chinese test suite. The performance is better than state-of-the-art results with an average F-measure of 0.80. The experiment verifies the value of VW for unsupervised method in WSD.