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The range of polysemous words as the object of the computer automatic word sense disambiguation is delimited. 先界定了作为计算机自动词义消歧对象的多义词的范围；
Abstract: Word sense disambiguation is a key problem and one of difficult points in natural language processing. 摘要：词义消歧一直是自然语言处理领域的关键问题和难点之一。
The rate of correct word sense disambiguation is over 98 % in the closed test, and over 96% in the open test. 词义消歧的精确率，封闭测试高达98%25以上，开放测试高达96%25以上。
Word sense disambiguation is one of the difficult problems in natural language processing. 摘要词义消歧是自然语言处理中的难题之一。
Lots of semantic rules are obtained from the experiments, and are used to sense disambiguation. 经过实验,得到大量语义规则,并用其进行义项消歧实验,取得了较好的结果。
The problem of word sense disambiguation can be formalized to be a typical classify problem. 摘要词义消歧问题可以形式化为典型的分类问题。
As an important work in the field of Natural Language Processing, Word Sense Disambiguation (WSD) has been a research focus since 1950. 作为自然语言理解的一项基础工作，词义消歧(Word Sense Disambiguation, WSD)一直是研究的重点。
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。
Parallel corpus has valuable application in machine translation, bilingual dictionary compilation, word sense disambiguation and Cross-Lingual Information Retrieval. 除机器翻译方面的应用之外，平行语料库的建设对于双语词典编纂、词义消岐和跨语言信息检索也具有重要价值。
The paper puts forward an algorithm that can automatically learn sense-tagging-oriented transformative rules and presents a corresponding word sense disambiguation algorithm. 该文提出用于文本词义标注的转换规则自动获取算法及相应的词义排歧算法。
At last,the author put forwards the idea of empoldering a system of word sense disambiguation according the primary content of the thesis and some coding experiments of its core modules are conducted. 最后，根据本文所讨论的主要内容提出了一种汉语词义排歧系统的开发思路，并对其中一些模块进行了代码实现。
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. 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。
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 ad information retrieval. 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。
For the purpose of implementing automatic Chinese word sense tagging, this paper presents a new method for word sense disambiguation based on unsupervised machine learning strategies. 为实现汉语全文词义自动标注，本文采用了一种新的基于无指导机器学习策略的词义标注方法。
A WORD SENSE DISAMBIGUATION BASED ON X-BAR 基于X结构的词义选择
Only some ambiguous words are disambiguated objects in many word sense disambiguation researches at present.There practices have limitation in real application. 目前进行的很多词义消歧研究多采用凡个多义词作为试验测试对象，在实际应用方面存在着局限性。
statistical word sense disambiguation 统计词义消歧
unsupervised word sense disambiguation 无监督词义消歧
Word Sense Disambiguation(WSD) and tagging 词义消歧与标注
Knowledge without common sense counts for little. 光有学问而无常识，则这种学问无甚价值。