摘要
词义消歧(WSD)一直是自然语言理解中的一个关键问题,该问题解决的好坏直接关系到自然语言处理中诸多应用问题的效果优劣。本文对大规模真实文本进行了词义消歧研究,采用了基于依存分析改进贝叶斯分类模型的有指导词义消歧方法。
Word sense disambiguation（WSD） is the key problem in natural language processing because the result of WSD affects many problems seriously in natural language processing and information retrieval. In this paper,large-scale real texts about word sense disambiguation are studied,and supervised word sense disambiguation approach is adopted based on dependency relation analysis and Bayes classifier.
