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Title: GitHub - javaver/word: Java分布式中文分词组件 - word分词

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Description: Java分布式中文分词组件 - word分词. Contribute to javaver/word development by creating an account on GitHub.

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捐赠致谢	https://github.com/ysc/QuestionAnsweringSystem/wiki/donation
word 1.0 API	http://apdplat.org/word/apidocs/1.0/
word 1.1 API	http://apdplat.org/word/apidocs/1.1/
word 1.2 API	http://apdplat.org/word/apidocs/1.2/
word 1.3 API	http://apdplat.org/word/apidocs/1.3/
编译好的jar包下载	http://pan.baidu.com/s/1dDziDFz
ForElasticsearch1.7.2	https://github.com/ysc/word/tree/ForElasticsearch1.7.2/
lukeall-4.0.0-ALPHA-with-word-1.0.jar	http://pan.baidu.com/s/1bn52ooR
lukeall-4.10.3-with-word-1.2.jar	http://pan.baidu.com/s/1mgFt7ZU
1、中文分词算法之基于词典的正向最大匹配算法	http://yangshangchuan.iteye.com/blog/2031813
2、中文分词算法之基于词典的逆向最大匹配算法	http://yangshangchuan.iteye.com/blog/2033843
3、中文分词算法之词典机制性能优化与测试	http://yangshangchuan.iteye.com/blog/2035007
4、中文分词算法之基于词典的正向最小匹配算法	http://yangshangchuan.iteye.com/blog/2040423
5、中文分词算法之基于词典的逆向最小匹配算法	http://yangshangchuan.iteye.com/blog/2040431
6、一种利用ngram模型来消除歧义的中文分词方法	http://my.oschina.net/apdplat/blog/411112
7、一种基于词性序列的人名识别方法	http://my.oschina.net/apdplat/blog/411032
8、中文分词算法之基于词典的全切分算法	http://my.oschina.net/apdplat/blog/412785
9、9大Java开源中文分词器的使用方法和分词效果对比	http://my.oschina.net/apdplat/blog/412921
10、中文分词之11946组同义词	http://my.oschina.net/apdplat/blog/408779
11、中文分词之9271组反义词	http://my.oschina.net/apdplat/blog/411301
12、如何利用多核提升分词速度	http://my.oschina.net/apdplat/blog/414076
13、利用word分词来计算文本相似度	http://my.oschina.net/apdplat/blog/417047
14、利用word分词来对文本进行词频统计	http://my.oschina.net/apdplat/blog/417641
15、利用word分词通过计算词的语境来获得相关词	http://my.oschina.net/apdplat/blog/417922
Java开源项目cws_evaluation：中文分词器分词效果评估对比	https://github.com/ysc/cws_evaluation/
Java开源项目QuestionAnsweringSystem：人机问答系统	https://github.com/ysc/QuestionAnsweringSystem/
Java开源项目word_web：通过web服务器对word分词的资源进行集中统一管理	https://github.com/ysc/word_web/
An Implementation of Double-Array Trie	http://linux.thai.net/~thep/datrie/datrie.html
MMSEG: A Word Identification System for Mandarin Chinese Text Based on Two Variants of the Maximum Matching Algorithm	http://technology.chtsai.org/mmseg/
With Google’s new tool Ngram Viewer, you can visualise the rise and fall of concepts across 5 million books and 500 years!	https://books.google.com/ngrams
word2vec	https://code.google.com/p/word2vec/
魅力汉语	http://open.163.com/special/cuvocw/meilihanyu.html
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