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Description: （1）从已经标注好词性的语料中统计得到词性标记的二元转移矩阵，以及每个词以确定的词性标记出现的次数等数据（训练阶段）
（2）利用动态规划算法快速选取词性标记路径，得到词性标记结果
（3）可以选择不同的词性标记集
-(1) from the good part-of-speech tagging has been the Corpus statistics to be part of speech marking the transfer of binary matrix, and every word to identify the markings of POS data, such as the number (training phase) (2) using dynamic programming algorithm is fast POS markers selected path, to be part-of-speech tags Results (3) can choose different POS tagset
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Size: 773120 |
Author: 赵阳 |
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Description: 词性标注与隐马尔可夫模型.ppt，相当好的说明材料。-part-of-speech tagging and Hidden Markov Model. Ppt, very good descriptive material.
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Size: 149504 |
Author: 郝云龙 |
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Description: 中文词性标注子程序第一步，将测试文本加入词性标记集、词语标记集、标记同现集，VFP源码-Chinese POS Tagging subroutine first step, the text will be tested by adding part of speech tag set, the word tag set, tag with the current set, VFP source
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Size: 1024 |
Author: 民民 |
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Description: 中文词性标注子程序第一步，将测试文本加入词性标记集、词语标记集、标记同现集，VFP源码.. -Chinese POS Tagging subroutine first step, the text will be tested by adding part of speech tag set, the word tag set, tag with the current set, VFP source ..
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Size: 12288 |
Author: 金凤龙 |
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Description: 中文词性标注子程序第一步，将测试文本加入词性标记集、词语标记集、标记同现集，VFP源码.. -Chinese POS Tagging subroutine first step, the text will be tested by adding part of speech tag set, the word tag set, tag with the current set, VFP source ..
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Size: 2174976 |
Author: 金凤龙 |
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Description: ICT分词程序接口
用以进行中文文本分词，词性标注。-ICT segmentation program interface for the conduct of the Chinese text word segmentation, POS tagging.
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Size: 6732800 |
Author: ellen |
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Description: 包含了词条及其词性标记，频度信息的词典 练语料的格式要求：
每个词以 / 分隔， / 后是该词的词性标记。词性标记后至少要有一个空格。一个句子的所有词必须在同一行中。击“开始词性标注”选取文本文件（一次可以选择多个）进行标注处理-Includes a term and its part of speech marks, the frequency of information and training Corpus dictionary format requirements: Each word in/separated/post is part of speech marking term. POS tag at least one space after. A sentence of all the words must be in the same line. Hit Start-of-speech tagging select text file (one can select multiple) to mark deal
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Size: 174080 |
Author: 张耀 |
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Description: 对中文进行分词并对其词性标注；命名实体识别；新词识别；同时支持用户词典-To be conducted in Chinese word segmentation and POS tagging Named Entity Recognition new word identification simultaneously support the user dictionary
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Size: 55296 |
Author: ictclas |
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Description: 学习汉语自动分词与词性标注软件的组件化有助于更好的理解中文分词系统-PoS tagging HMM
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Size: 125952 |
Author: xuxianglan0404 |
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Description: 中科院中文进行分词并对其词性标注；命名实体识别；新词识别；同时支持用户词典-Chinese Academy of Sciences Chinese word segmentation and POS tagging named entity recognition new word identification At the same time support the user dictionary
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Size: 50176 |
Author: hjh |
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Description: 用c++实现了词性标注功能
，这是机器翻译过程中极其初级的一部-Achieve part of speech tagging functionality
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Size: 8100864 |
Author: 王忠存 |
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Description: 处理的对象是：完成分词和词性标注的语料，实现的结果是：统计出现词频完成降序排列。-Dealing with the object are: the completion of word segmentation and POS tagging of the corpus, the results achieved are: the completion of word frequency statistics appear in descending order.
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Size: 36864 |
Author: 陈烨彬 |
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Description: 词性标注。首先根据预料库训练模型，然后用得到的模型对未标记词性的语句进行词性标注。-Part of Speech Tagging. First, according to the training model is expected to libraries, and then get the model right part of speech of the statement is not marked for POS Tagging.
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Size: 8878080 |
Author: 秦佳佳 |
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Description: 哈工大LTP自然语言处理工具的java调用实例，利用jni调用dll，实现中文的分词，词性标注，建立依存树等-HIT LTP natural language processing tool called an instance of java using jni call the dll, to achieve in Chinese word segmentation, POS tagging, the establishment of dependency trees, etc.
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Size: 1008640 |
Author: zhangcheng |
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Description: 句法分析器的一个Windows可执行文件，其用法：1. 先打开规则库，读入规则集 （规则文件放在 \rule目录下）
2. 选择经过分词和词性标注的文件，进行句法分析 （测试文件放在 \test目录下）
3. 分析结果文件与测试文件在同一个目录下，文件后缀名为 .pcfg
4. 可以观察规则概率值和期望次数的变化
5. 分析结果逐个以树形图方式显示，如果一个句子有多个结果，在显示框中同时显示。
-Parser a Windows executable file, its usage: 1. The first rule base open, read into the rule set (rule files in \ rule directory) 2. Selection through segmentation and POS tagging of the document for syntactic analysis (test file on the \ test directory) 3. Analysis of the results file with the test file in the same directory, the file name suffix. pcfg 4. to observe the rules of probability values and expectations of changes in the number 5. Analysis of the results one by one by way of tree shows that if a sentence has multiple results, shown in the display box at the same time.
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Size: 182272 |
Author: 贝 |
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Description: ICTCLAS分词的总体流程包括：1）初步分词；2）词性标注；3）人名、地名识别；4）重新分词；5）重新词性标注这五步。就第一步分词而言，又细分成：1）原子切分；2）找出原子之间所有可能的组词方案；3）N-最短路径中文词语粗分三步。
在所有内容中，词典库的读取是最基本的功能。ICTCLAS中词典存放在Data目录中，常用的词典包括coreDict.dct（词典库）、BigramDict.dct（词与词间的关联库）、nr.dct（人名库）、ns.dct（地名库）、tr.dct（翻译人名库），它们的文件格式是完全相同的，都使用CDictionary类进行解析。如果想深入了解ICTCLAS词典结构，可以参考sinboy的《ICTCLAS分词系统研究（二）--词典结构》一文，详细介绍了词典结构。
-ICTCLAS word of the overall process include: 1) initial segmentation 2) POS tagging 3) names, places identification 4) to re-word 5) This five-step re-speech tagging. The first word, the thin, divided into: 1) atom splitting 2) to identify all the possible atomic set of words between the program 3) N-shortest paths Chinese words rough three steps.
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Size: 1965056 |
Author: ounata |
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Description: ctbparser是一个开源的中文句法分析工具包，用于分词、词性标注、依存句法分析-ctbparser is an open source Chinese parsing toolkit for Chinese word segmentation, POS tagging, dependency parsing
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Size: 14619648 |
Author: qianxian |
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Description: ctbparser是一个开源的中文句法分析工具包，用于分词、词性标注、依存句法分析-ctbparser is an open source Chinese parsing toolkit for Chinese word segmentation, POS tagging, dependency parsing
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Size: 14977024 |
Author: qianxian |
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Description: 实现了中文分词和词性标注程序。分词方法采用“三词正向最长匹配”。词性标注使用HMM方法，用Viterbi算法实现。“三词正向最长匹配”保持了“正向最长匹配算法”快速的特点，同时提高了分词的准确性。-Chinese word segmentation and implemented procedures for POS tagging. Segmentation Methods, " the longest three-match positive words." POS tagging using HMM method, the Viterbi algorithm. " Three words maximum positive match" to maintain a " positive maximum matching algorithm," Fast features, while improving the accuracy of segmentation.
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Size: 4034560 |
Author: paul |
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Description: 基于隐马尔科夫的中文词性标注系统的C++源代码，包括训练集和测试集语料库，单词量和词性数目都没有写死，可适应任意大的训练和测试数据集，程序已经过优化，一次标注只需要不到10秒的时间。-Based on Hidden Markov of the Chinese part of speech tagging system in C++ source code, including the training set and test set corpus, vocabulary and speech numbers are not coded, can be adapted to arbitrarily large training and test data sets, the program has been optimized, a mark only need less than 10 seconds.
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Size: 4440064 |
Author: 蒋智威 |
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