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汉语自动分词与词性标注软件中文分词系统
- 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
Chinese-Word-Segment-And-POS-Tagger
- 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 tag
PoS-Tagging-based-on-HMM
- 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
Unsupervise
- 利用隐马尔可夫模型实现词性标注。此为无监督模型。 内含语料库和测试集。方便大家学习。-The use of Hidden Markov Model to achieve part of speech tagging. This is no oversight model. Corpus and the test set contains. To facilitate them to learn.
keyword-chouqu
- 基于逆向最大匹配算法的分词及基于HMM模型的词性标注系统，包括了未登录词的识别、数据库的添加等内容。（需要手动修改数据库的路径才可以运行）-Reverse Maximum Matching Algorithm Based on the sub-word HMM-based model and part of speech tagging system, including the unknown word identification, such as the contents of the d
hmmfan
- 一个用于 词性标注的 HMM程序。 包含 训练和测试功能。-One for the HMM-speech tagging procedures. Includes training and testing.
fenci
- 基于HMM的词性标注程序，包含了HMM思想的核心，稍作修改就可以移植-HMM-based speech tagging process, including the ideological core of HMM, a little modification can be transplant
HMM
- 基于应隐马尔科夫模型的词性标注实现，Viterbi算法实现 -Should be based on hidden Markov models to achieve part of speech tagging, Viterbi algorithm
Rkeyword-choue
- 基于逆向最大匹配算法的分词及基于HMM模型的词性标注系统，包括了未登登录词的识别、数据库的添加等内容。（需要手动修改数据库的路径才可以运行） -Based on the segmentation of the reverse maximum matching algorithm and the HMM-based POS tagging system, including unadvertised login word recognition, and add the database co
HMMparse
- HMM词性标注，使用MFC界面，标注效果好，供有兴趣的同学们参考-Part-of-speech tagging by using HMM
nlu_project
- 采用机器学习的方法进行自然语言处理，对中文进行分词和词性标注。分词采用crf模型，词性标注用hmm模型，解码算法为Vertibi算法。本系统使用java语言编写-Using machine learning methods for natural language processing, carried out on the Chinese word segmentation and POS tagging. Segmentation using crf model, tagging with
0nlu_project
- 本系统使用java语言编写,采用机器学习的方法进行自然语言处理，对中文进行分词和词性标注。分词采用crf模型，词性标注用hmm模型，解码算法为Vertibi算法。-The system uses java language, using machine learning methods for natural language processing, for Chinese word segmentation and POS tagging. Segmentation using crf mod
HmmPos
- 基于HMM的中文词性标注代码，内有详细注释，并附有练习样本-Chinese POS tagging HMM-based code, with detailed notes, along with sample exercises
hmm机器学习
- HMM(隐马尔科夫模型)是自然语言处理中的一个基本模型，用途比较广泛，如汉语分词、词性标注及语音识别等，在NLP中占有很重要的地位(HMM (hidden Markov model) is a basic model in Natural Language Processing, which is widely used, such as Chinese segmentation, part of speech tagging and speech recognition, and plays
HMM-master
- python实验中文词性标注,包括预处理，实验数据为新闻语料。(Chinese word pos-of-speech with python)