Lastly , an automation classifying system is established combining the classifying methods of knn , naive bayes and simple vector space , which validates the efficiency of the word segmentation method 在第三章分词的基础之上，结合knn , na ( ? ) vebayes和简单向量距离分类算法，建立了一个基于分词的自动分类系统。
The proper nouns usually derives new words frequently , easy to change or disappear , and can not be formed following particular rules , all of these cause the proper nouns hard to be recognized in the sentence and make chinese word segmentation difficult 专有名词存在新词出现快,成词无固定规则,容易变化等特点,给汉语分词带来了很大的干扰,使专有名词的识别成为汉语分词的一大瓶颈。
The automatic and accurate identification of chinese organization names is very significant to improve the accuracy of automatic word segmentation , and it will establish a good foundation for natural language comprehension , machine translation , information extraction and information retrieval 中文机构名称的自动识别对提高汉语自动分词的精确率有着重要的意义，也是自然语言理解、机器翻译、信息抽取和信息检索的基础。
Refer to chinese automatic word segmentation based on statistics , this paper imports the mechanism of open learning , and uses the method of supervised and unsupervised learning . the word segmentation model includes credibility revising and partial tri - gram information 本文在基于统计的汉语自动分词的基础上，引入开放学习机制，通过有监督和无监督相结合的学习方法，建立包含可信度修正和部分三元语法信息的多元分词模型。
Chinese information processing model is added to the traditional search engine , which can make search engine intelligent and personalized . chinese automatic word segmentation is the first work in chinese information processing . in this paper , a chinese word segmentation system is studied , which fits for intelligence search engine 针对歧义字段的划分问题，提出了歧义字段划分的三个原则，在三原则的基础上给出了“二字续分法”分词的方案，该方案能够快速有效的分解大部分的歧义字段，具有很高的实用价值。
Chinese automatic word segmentation is the fundamental task of the chinese information processing . it mainly comprises of three difficult questions , including word criterion , disambiguation , unknown word identifying . many researchers have contributed to this field , but in the present days , it still needs pursuing higher precision 汉语自动分词是中文信息处理领域的基础课题,而且也是进行其它中文信息处理的前提,它有三个主要难点分别是分词规范,歧义字段切分和未登录词,国内外许多研究人员在这一领域都进行了深入的研究,但就目前现状来看,分词的正确率仍然有提升的空间。
This paper bases on chinese word cut which impenetrate the programme bring the paper to pass . this paper exhausted the function of chinese word cut in detail besides how to classify the sub - classification of quantifiers and nouns in modern chinese , the match relationship between quantifiers and nouns and the way finding out the errors of these match relationship in a chinese text . the final segment of this paper still pointed out the draw back of my paper and submited several possible solutions 我所做的量词和名词的搭配及查错是在汉语分词的基础上实现的，分词贯穿了量词和名词的搭配及查错的全过程，所以本文先是在介绍了现代汉语名词和量词的子类划分之后，对汉语词汇分析的特点和难点、数量结构对汉语分词的影响做了详细的阐述，正是这些部分对我所设计的程序性能有很重要的影响。
It discusses and analyzes about automatic word segmentation methods for the chinese language emphatically . moreover it gives the application expectation among this system a method of word segmentation based on the reverse directional maximum matching method . it also proposes that the key of the word segmentation still needs an intact and rational word segmentation dictionary 本文首先研究和讨论了基于自然语言的语义分析方法，对汉语的自动分词方法进行了着重讨论和分析，并给出了一种基于反向最大匹配法的分词方法在本系统中的应用展望，提出分词的关键还需要一个完整合理的分词词典。
