Abstract:multi-senses of a word are widespread phenomenon in the natural language.The accuracy rate of sense ambiguation is the most important target of a software on the fields of machine translation, information indexing and text sorting.A method based on the bayes and machine readable dictionary was proposed, which could disambiguate by the training of a small-scale corpus and the definition of semantic in machine dictionary.The experimental results show that it has a high accuracy rate of word sense ambiguation when the scale of markup corpus has been limited.
谈文蓉; 符红光; 刘莉; 杨宪泽. 一种基于贝叶斯分类与机读词典的多义词排歧方法[J]. 计算机应用, 2006, 26(6): 1389-1391.
WenRong Tan;;;. Method of word sense disambiguation based on bayes and machine readable dictionary. Journal of Computer Applications, 2006, 26(6): 1389-1391.