First of all, the significance of unsupervised word sense disambiguation study is introduced.
首先，介绍了无监督词义消歧研究的意义。
The goal of this paper is to give a brief summary of the current unsupervised word sense disambiguation techniques in order to facilitate future research.
研究的目的是对现有的无监督词义消歧技术进行总结，以期为进一步的研究指明方向。
The Word Sense Disambiguation (WSD) study based on large scale real world corpus is performed using an unsupervised learning algorithm based on DGA improved Bayesian Model.
采用基于依存分析改进贝叶斯网络的无指导的机器学习方法对汉语大规模真实文本进行词义消歧实验。
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