word segmentation

The Study and Realization of Word Segmentation of Database Chinese Query Language

数据库汉语查询语言的分词研究与实现

It is the primary key technical link in natural language processing. The current technology of Chinese word segmentation is working for Chinese text.

它是自然语言处理过程中首要的技术环节，其重要性不言而喻。目前的中文分词技术主要针对中文文本进行分词。

For Chinese natural language processing, Chinese word segmentation is the first step in text analysis.

对于汉语的自然语言处理来说，汉语自动分词是文本分析的第一个步骤。

The whole process of text representation were discussed& word segmentation, building stop words list, feature selection, weight computation and generating vector space.

讨论了文本表示的整个过程&分词，建立停用词表，特征选择，权重计算，生成向量空间。

Others such as machine translation ( MT), speech synthesis, automatic classification, automatic summarization, automatic proofreading etc., require the use of word segmentation.

其他的比如机器翻译（MT）、语音合成、自动分类、自动摘要、自动校对等等，都需要用到分词。

With the CRFs of Chinese word segmentation, using Chinese word tagging method for automatic Chinese word segmentation system.

接着本文描述了将条件随机场用于汉语分词，采用汉字标注的分词方法及基于CRFs的中文自动分词系统的实现。

We use the Chinese word segmentation approach based on melody database to create a music melodic contour database.

在旋律音高序列的基础上运用中文分词的方法，建立音乐词旋律轮廓库。

Automatic Segmentation and POS ( Part-of-speech) tagging directly impact on the named entity recognition. This paper used the Massive Intelligent Segmentation system to the text word segmentation and Tagging.

自动分词和词性标注直接影响命名实体的识别，本文采用了海量智能分词系统对文本进行分词和标注。

First, three common word segmentation dictionary systems and the dictionary system based on double-character-hash-indexing, Patricia tree and four-character-hash-indexing are studied and explored. Some questions are found in these systems and the unreasonable structures are improved.

本文对三种典型的分词词典机制、基于双字哈希的词典机制、基于PAT树的词典机制及四字哈希词典机制进行了探讨与研究，并针对这些机制存在的问题提出了改进措施。

In text analysis module, this paper studies Vietnamese word segmentation, part-of-speech ( POS) tagging, text normalization, prosody phrase ( L3) break prediction and so on.

在前端文本分析方面，本文研究越南语的分词、词性标注、特殊符号处理和韵律短语（L3）边界预测等关键技术。

Application of Katz Smoothing in Chinese Word Segmentation System

Katz平滑算法在中文分词系统中的应用

The proposed algorithm has already been applied in our Web answering system, the experimental result shows that it has high accuracy and efficiency of word segmentation and elimination of the ambiguity of words segmentation.

该算法已经在基于Web的自然语言答疑系统WebAnswerSystem中实现并得到了实际应用。实验结果表明，算法具有较高的准确率和召回率，对自然语言网络答疑中进行切分歧义消除是行之有效的。

In test of crossing word segmentation disambiguation, correct rate is over 94%, average wrong rate is 25% lower than that of ICTCLAS system developed by the Institute of Computation in China Academy of Science.

交集型切分真歧义的消解不但精确率普遍在94%以上，而且平均错误率也比ICTCLAS系统低25%以上。

The processing of Chinese corpus includes Chinese word segmentation and part-of-speech tagging.

汉语语料的基本加工过程,包括自动分词和词性标注两个阶段.

The paper proposes an approach to language independent text classification without word segmentation.

本文提出了一种独立于语种不需分词的文本分类方法。

At the same time, we apply the statistics method to identify the new words that are inexistent in the dictionary and supply them to the dictionary for the later text word segmentation.

同时应用统计方法识别出词典中没有的新词，并将其补充进词典中，用于切分后续文本。

According to the mobile terminal operation ability and storage capacity, this paper does not use large participle word library, but the simple Bigram word segmentation method, we make pretreatment by means of removing stop words segmentation, get the message content feature vector.

针对移动终端的运算能力和存储能力，本文没有采用大型的分词词库，而是采用简单易行的Bigram分词方法，通过去除停用词等手段对分词结果进行预处理，得到短信内容的特征向量。

Summarize all kinds of difficulties encountered in the process and give the evaluation standard for Chinese word segmentation. ( 3) The core indicator of word segmentation is speed and accuracy.

对在中文分词过程中所遇到的困难进行了概括并给出了评价中文分词的标准。（3）分词速度和精度是衡量分词系统的核心指标。

Chinese text automatic word segmentation technology is an important link of Chinese information processing, Chinese text automatic word segmentation algorithm for Chinese word segmentation are closely related to the performance of the system.

中文文本自动分词技术是中文信息处理的重要环节，中文文本自动分词算法与中文分词系统的性能紧密相关。

But can be expected, when the document database contains a very large amount of information, the time and space must also be at quite large costs for doing text pretreatment, Chinese word segmentation and making indexed database.

但是可以预想，当文档库所包含的信息量非常大，对文档全部内容进行预处理，再分词建立索引库，时空耗费必然也相当庞大。

Expert search module, the user input a query, system use the chinese word segmentation to segment query into multiple query terms, for each query term search and match expert feature in the database, read the value as the expert evaluation score on the query word.

用户检索，用户输入查询后，使用中文分词技术切分查询成多个查询词，对于每个查询词从专家特征库中搜索匹配特征，读取特征值作为对专家关于该查询词的评价得分。

They are the segmentation effect test, word accuracy test, test of Onomastics identification, word segmentation speed test and resource overhead test.

它们分别是分词效果测试、分词准确率测试、人名识别和地名识别测试、分词速度测试和资源开销测试。

The results show that the rate of correctly disambiguating covering word segmentation ambiguity is over 99% in the closed test and 87.84% in the open test.

结果表明，组合型切分歧义消解的精确率比ICTCLAS系统有了进一步提高，封闭测试精确率在99%以上，开放测试的精确率为87.84%。

This paper presents an algorithm based on the combination of Support Vector Maching ( SVM) and k Nearest neighbor ( k NN), to deal with ambiguities in Chinese word segmentation.

本文提出了基于支持向量机（SVM）和k近邻（kNN）相结合的一种分类方法，用于解决交集型伪歧义字段。

Character-Based Tagging: A New Method for Chinese Word Segmentation

由字构词&中文分词新方法

The ACL-SIGHAN sponsored the First International Chinese Word Segmentation in July, 2003 in Japan.

2003年在日本札幌举行了第一届ACL-SIGHAN国际中文分词竞赛。

Different from English, there are no interval marks between words in Chinese, so it is difficult for word segmentation to identify ambiguous words.

汉语不同于英语，词之间没有间隔标记。而汉语分词是文本分析的第一步，且存在歧义切分，因此分词问题成为汉语分析的首要难题。

We first analysis the characteristic of HTML documents, then discuss the key technique of automatic text classification, including Vector Space Model, Chinese word segmentation, text feature selection, and implement a multinomial NaiVe Bayes classifier to classify Chinese Web page.

本文首先分析了Web页面的组织特点，对文本自动分类中使用到的向量空间模型、分词、特征选择等关键技术进行了深入的探讨，并实现了一个多项式朴素贝叶斯分类器对中文网页进行分类。

The Chinese word segmentation and the matching algorithm based on keywords are adopted for the prototype design of Chinese chat robots.

探讨了中文聊天机器人原型系统的设计方式，提出了采用中文分词与关键词语匹配算法。

According to the structure and storage of the directory, we design and apply a word segmentation algorithm on the text to segment the words and label the features.

然后使用一种适合目录信息的结构和存储格式的分词方法，对目录文本进行分词处理并对目录信息中的特征项进行标注。