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"结巴"中文分词：做最好的Python中文分词组件 "Jieba" (Chinese for "to stutter") Chinese text segmentation: built to be the best Python Chinese word segmentation module.

News

支持国产开源软件，为结巴分词投一票，谢谢:-), 投票地址： https://code.csdn.net/2013ossurvey

Feature

在线演示

http://jiebademo.ap01.aws.af.cm/

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网站代码：https://github.com/fxsjy/jiebademo

Python 2.x 下的安装

Python 3.x 下的安装

Algorithm

功能 1)：分词

代码示例( 分词 )

#encoding=utf-8
import jieba

seg_list = jieba.cut("我来到北京清华大学", cut_all=True)
print "Full Mode:", "/ ".join(seg_list)  # 全模式

seg_list = jieba.cut("我来到北京清华大学", cut_all=False)
print "Default Mode:", "/ ".join(seg_list)  # 精确模式

seg_list = jieba.cut("他来到了网易杭研大厦")  # 默认是精确模式
print ", ".join(seg_list)

seg_list = jieba.cut_for_search("小明硕士毕业于中国科学院计算所，后在日本京都大学深造")  # 搜索引擎模式
print ", ".join(seg_list)

Output:

【全模式】: 我/ 来到/ 北京/ 清华/ 清华大学/ 华大/ 大学

【精确模式】: 我/ 来到/ 北京/ 清华大学

【新词识别】：他, 来到, 了, 网易, 杭研, 大厦    (此处，“杭研”并没有在词典中，但是也被Viterbi算法识别出来了)

【搜索引擎模式】： 小明, 硕士, 毕业, 于, 中国, 科学, 学院, 科学院, 中国科学院, 计算, 计算所, 后, 在, 日本, 京都, 大学, 日本京都大学, 深造

功能 2) ：添加自定义词典

功能 3) ：关键词提取

代码示例 （关键词提取）

https://github.com/fxsjy/jieba/blob/master/test/extract_tags.py

功能 4) : 词性标注

功能 5) : 并行分词

其他词典

  1. 占用内存较小的词典文件 https://github.com/fxsjy/jieba/raw/master/extra_dict/dict.txt.small

  2. 支持繁体分词更好的词典文件 https://github.com/fxsjy/jieba/raw/master/extra_dict/dict.txt.big

下载你所需要的词典，然后覆盖jieba/dict.txt 即可或者用jieba.set_dictionary('data/dict.txt.big')

模块初始化机制的改变:lazy load （从0.28版本开始）

jieba采用延迟加载，"import jieba"不会立即触发词典的加载，一旦有必要才开始加载词典构建trie。如果你想手工初始jieba，也可以手动初始化。

import jieba
jieba.initialize()  # 手动初始化（可选）

在0.28之前的版本是不能指定主词典的路径的，有了延迟加载机制后，你可以改变主词典的路径:

jieba.set_dictionary('data/dict.txt.big')

例子： https://github.com/fxsjy/jieba/blob/master/test/test_change_dictpath.py

分词速度

常见问题

1）模型的数据是如何生成的？https://github.com/fxsjy/jieba/issues/7

2）这个库的授权是? https://github.com/fxsjy/jieba/issues/2

更多问题请点击：https://github.com/fxsjy/jieba/issues?sort=updated&state=closed

Change Log

https://github.com/fxsjy/jieba/blob/master/Changelog

jieba

"Jieba" (Chinese for "to stutter") Chinese text segmentation: built to be the best Python Chinese word segmentation module.

Features

Usage

Algorithm

Function 1): cut

Code example: segmentation

#encoding=utf-8
import jieba

seg_list = jieba.cut("我来到北京清华大学", cut_all=True)
print "Full Mode:", "/ ".join(seg_list)  # 全模式

seg_list = jieba.cut("我来到北京清华大学", cut_all=False)
print "Default Mode:", "/ ".join(seg_list)  # 默认模式

seg_list = jieba.cut("他来到了网易杭研大厦")
print ", ".join(seg_list)

seg_list = jieba.cut_for_search("小明硕士毕业于中国科学院计算所，后在日本京都大学深造")  # 搜索引擎模式
print ", ".join(seg_list)

Output:

[Full Mode]: 我/ 来到/ 北京/ 清华/ 清华大学/ 华大/ 大学

[Accurate Mode]: 我/ 来到/ 北京/ 清华大学

[Unknown Words Recognize] 他, 来到, 了, 网易, 杭研, 大厦    (In this case, "杭研" is not in the dictionary, but is identified by the Viterbi algorithm)

[Search Engine Mode]： 小明, 硕士, 毕业, 于, 中国, 科学, 学院, 科学院, 中国科学院, 计算, 计算所, 后, 在

, 日本, 京都, 大学, 日本京都大学, 深造

Function 2): Add a custom dictionary

Function 3): Keyword Extraction

Code sample (keyword extraction)

https://github.com/fxsjy/jieba/blob/master/test/extract_tags.py

Using Other Dictionaries

It is possible to supply Jieba with your own custom dictionary, and there are also two dictionaries readily available for download:

  1. You can employ a smaller dictionary for a smaller memory footprint: https://github.com/fxsjy/jieba/raw/master/extra_dict/dict.txt.small

  2. There is also a bigger file that has better support for traditional characters (繁體): https://github.com/fxsjy/jieba/raw/master/extra_dict/dict.txt.big

By default, an in-between dictionary is used, called dict.txt and included in the distribution.

In either case, download the file you want first, and then call jieba.set_dictionary('data/dict.txt.big') or just replace the existing dict.txt.

Initialization

By default, Jieba employs lazy loading to only build the trie once it is necessary. This takes 1-3 seconds once, after which it is not initialized again. If you want to initialize Jieba manually, you can call:

import jieba
jieba.initialize()  # (optional)

You can also specify the dictionary (not supported before version 0.28) :

jieba.set_dictionary('data/dict.txt.big')

Segmentation speed

Online demo

http://jiebademo.ap01.aws.af.cm/

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