搜索资源列表
OrgTag
- 分词词典软件,采用HMM方法同时在HMM识别后再次用规则对结果进行优化,优化专门针对商业机构。-dictionary software, the method used in HMM HMM identification rules used again after the results of optimization, Optimization of specific businesses.
fenci
- 分词程序,HMM模型训练,维特比解码,有说明文档。
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
HMM
- 基于统计的分词,采用隐马尔可夫模型,并有实验报告-Based on statistics segmentation using hidden Markov models, and there is experimental report
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
HMMWordsDivideCsharp
- 隐马分词源代码(Csharp解决方案) -Csharp HMM隐马分词源代码(Csharp解决方案)
Segmentation
- 用HMM实现的中文分词程序,用C#实现的。-HMM to achieve with the Chinese word segmentation
wordSegment
- 汉语分词 隐马尔科夫模型 最大匹配法 最大概率法-HMM MaxMatch
imdict-chinese-analyzer
- imdict-chinese-analyzer 是 imdict智能词典 的智能中文分词模块,算法基于隐马尔科夫模型(Hidden Markov Model, HMM),是中国科学院计算技术研究所的ictclas中文分词程序的重新实现(基于Java),可以直接为lucene搜索引擎提供简体中文分词支持。-imdict-chinese-analyzer is a smart imdict Chinese Dictionary smart module segmentation algorithm
Sfenciie
- 分词程序,HMM模型训练,维特特比解码,有说明文档。可直接使用。 -Segmentation process, HMM model training, Viterbi decoding, and documentation. Complete source code can be used directly.
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
fenci
- 利用HMM,针对《1998年人民日报》语料库进行研究,最终实现了中文语句的自动分词-By HMM, research, and ultimately the Chinese statement for the 1998 People' s Daily " Corpus automatic segmentation
hmmWordSegmentation
- 这是一个基于hmm模型的句子分词程序,语言是python,目前输入语句不支持标点符号。-This program is for divising a sentence into seperate words base on 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
matching-Chinese-word-by-HMM-and-MM
- 该程序为在MFC下开发的正向和反向两种中文分词系统。-The program was developed in MFC under both positive and negative Chinese word segmentation system.
CWSS17.1.1.4
- 基于隐马尔科夫模型的中文分词系统,上交ieee专业大一作业,界面一般,主要用于学习,在此分享,注:开发环境python3.5(Based on Hidden Markov model of Chinese word segmentation system, on the IEEE professional freshman job, interface is common, mainly used for learning, in this share, note: development en
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
24.HMM
- 通过hmm实现中文分词,并且能自动发现新词的功能(The Chinese word segmentation is realized by HMM, and the function of new words can be automatically found)
Pinyin2Hanzi
- DAG表示基于分词的拼音输入法,正确率一般,viterbi是HMM模型(DAG is a Pinyin input method based on participle, and the accuracy rate is general. Viterbi is a HMM model.)
HMM-master
- 隐马尔科夫模型进行中文分词 模型训练 python HMM_train.py RenMinData.txt_utf8 RenMinData.RenMinData_utf8 为人民日报已经人工分词的预料。 生成三个文件 * prob_start.py 为模型的初始概率 * prob_trans.py 为模型状态转移概率 * prob_emit.py 为发射概率 测试模型效果 python HMM.py reference 维特比算法:(python