自然语言处理资源大全

https://github.com/HIT-SCIR/pyltp

http://ltp.readthedocs.io/zh_CN/latest/

http://blog.csdn.net/churximi/article/details/51174182

http://www.cnblogs.com/ybf-yyj/p/7658571.html

http://blog.csdn.net/churximi/article/details/51174182

http://www.cnblogs.com/anderslly/p/jiebanet.html

https://www.codeproject.com/Articles/32201/Lucene-Net-Custom-Synonym-Analyzer

https://github.com/linezero/jieba.NET

https://github.com/anderscui/jieba.NET

https://www.ltp-cloud.com/

https://github.com/chapzq77/LTP_Python_Interface

https://github.com/NLPchina/nlp-lang

https://github.com/NLPchina/ansj_seg

http://www.nlpcn.org/resource/list/4

https://github.com/sing1ee/jieba-solr

https://www.nuget.org/packages/jieba.NET

https://python.libhunt.com/project/snownlp/vs/jieba

https://github.com/FudanNLP/fnlp

https://github.com/hankcs/HanLP/

https://github.com/crownpku/awesome-chinese-nlp

https://www.codeproject.com/Articles/32175/Lucene-Net-Text-Analysis

http://lucenenet.apache.org/

https://github.com/apache/lucenenet

https://github.com/JimLiu/Lucene.Net.Analysis.PanGu

https://github.com/LonghronShen/OurAspNet.Lucene.Net.Analysis.PanGu

1.Chinese NLP Toolkits 中文NLP工具

Toolkits 综合NLP工具包

Popular NLP Toolkits for English/Multi-Language 常用的英文或支持多语言的NLP工具包

Chinese Word Segment 中文分词

Information Extraction 信息提取

QA & Chatbot 问答和聊天机器人

2.Corpus 中文语料

3.Organizations 相关中文NLP组织和会议

4.Learning Materials 学习资料

Chinese NLP Toolkits 中文NLP工具

Toolkits 综合NLP工具包

THULAC 中文词法分析工具包by 清华 (C++/Java/Python)

NLPIRby 中科院 (Java)

LTP 语言技术平台by 哈工大 (C++)

FudanNLPby 复旦 (Java)

BosonNLPby Boson (商业API服务)

HanNLP(Java)

SnowNLP(Python) Python library for processing Chinese text

YaYaNLP(Python) 纯python编写的中文自然语言处理包，取名于“牙牙学语”

DeepNLP(Python) Deep Learning NLP Pipeline implemented on Tensorflow with pretrained Chinese models.

chinese_nlp(C++ & Python) Chinese Natural Language Processing tools and examples

Chinese-Annotator(Python) Annotator for Chinese Text Corpus 中文文本标注工具

Popular NLP Toolkits for English/Multi-Language 常用的英文或支持多语言的NLP工具包

CoreNLPby Stanford (Java)

NLTK(Python)

spaCy(Python)

OpenNLP(Java)

gensim(Python) Gensim is a Python library for topic modelling, document indexing and similarity retrieval with large corpora.

Chinese Word Segment 中文分词

Jieba 结巴中文分词(Python) 做最好的 Python 中文分词组件

kcws 深度学习中文分词(Python) BiLSTM+CRF与IDCNN+CRF

ID-CNN-CWS(Python) Iterated Dilated Convolutions for Chinese Word Segmentation

Genius 中文分词(Python) Genius是一个开源的python中文分词组件，采用 CRF(Conditional Random Field)条件随机场算法。

loso 中文分词(Python)

Information Extraction 信息提取

MITIE(C++) library and tools for information extraction

Duckling(Haskell) Language, engine, and tooling for expressing, testing, and evaluating composable language rules on input strings.

IEPY(Python) IEPY is an open source tool for Information Extraction focused on Relation Extraction.

Snorkel: A training data creation and management system focused on information extraction

Neural Relation Extraction implemented with LSTM in TensorFlow

A neural network model for Chinese named entity recognition

Information-Extraction-ChineseChinese Named Entity Recognition with IDCNN/biLSTM+CRF, and Relation Extraction with biGRU+2ATT 中文实体识别与关系提取

QA & Chatbot 问答和聊天机器人

Rasa NLU(Python) turn natural language into structured data

Rasa Core(Python) machine learning based dialogue engine for conversational software

Chatterbot(Python) ChatterBot is a machine learning, conversational dialog engine for creating chat bots.

Chatbot(Python) 基於向量匹配的情境式聊天機器人

Tipask(PHP) 一款开放源码的PHP问答系统，基于Laravel框架开发，容易扩展，具有强大的负载能力和稳定性。

QuestionAnsweringSystem(Java) 一个Java实现的人机问答系统，能够自动分析问题并给出候选答案。

使用TensorFlow实现的Sequence to Sequence的聊天机器人模型(Python)

使用深度学习算法实现的中文阅读理解问答系统(Python)

DuReader中文阅读理解Baseline代码(Python)

Corpus 中文语料

开放知识图谱OpenKG.cn

大规模中文概念图谱CN-Probase公众号介绍

CLDC中文语言资源联盟

中文 Wikipedia Dump

98年人民日报词性标注库@百度盘

百度百科100gb语料@百度盘密码neqs 出处应该是梁斌penny大神

搜狗20061127新闻语料(包含分类)@百度盘

UDChinese(for training spaCy POS)

中文word2vec模型

中文word2vec模型之维基百科中文使用2017年6月20日中文维基百科语料训练的脚本和模型文件。

Synonyms:中文近义词工具包基于维基百科中文和word2vec训练的近义词库，封装为python包文件。

Chinese_conversation_sentimentA Chinese sentiment dataset may be useful for sentiment analysis.

中文突发事件语料库Chinese Emergency Corpus

dgk_lost_conv 中文对白语料chinese conversation corpus

用于训练中英文对话系统的语料库Datasets for Training Chatbot System

八卦版問答中文語料

中国股市公告信息爬取通过python脚本从巨潮网络的服务器获取中国股市（sz,sh）的公告(上市公司和监管机构)

tushare财经数据接口TuShare是一个免费、开源的python财经数据接口包。

保险行业语料库[52nlp介绍Blog] OpenData in insurance area for Machine Learning Tasks

最全中华古诗词数据库唐宋两朝近一万四千古诗人, 接近5.5万首唐诗加26万宋诗. 两宋时期1564位词人，21050首词。

DuReader中文阅读理解数据

中文语料小数据包含了中文命名实体识别、中文关系识别、中文阅读理解等一些小量数据

中文人名语料库中文姓名,姓氏,名字,称呼,日本人名,翻译人名,英文人名。

中文数据预处理材料中文分词词典和中文停用词

漢語拆字字典

Organizations 相关中文NLP组织和会议

中国中文信息学会

NLP Conference CalenderMain conferences, journals, workshops and shared tasks in NLP community.

Learning Materials 学习资料

中文Deep Learning Book

Stanford CS224n Natural Language Processing with Deep Learning 2017

Oxford CS DeepNLP 2017

Speech and Language Processingby Dan Jurafsky and James H. Martin

52nlp 我爱自然语言处理

hankcs 码农场

文本处理实践课资料文本处理实践课资料，包含文本特征提取（TF-IDF），文本分类，文本聚类，word2vec训练词向量及同义词词林中文词语相似度计算、文档自动摘要，信息抽取，情感分析与观点挖掘等实验。

https://github.com/crownpku/Awesome-Chinese-NLP

<自已动手构造编译系统》GCC

https://github.com/fanzhidongyzby/cit/

https://code.google.com/archive/p/redis/#!

https://github.com/antirez/redis/

https://github.com/rabbitmq

https://github.com/rabbitmq/rabbitmq-dotnet-client

https://www.microsoft.com/en-us/cognitive-toolkit/

http://www.csharpkit.com/

https://github.com/mathnet

https://marketplace.visualstudio.com/items?itemName=ms-toolsai.vstoolsai-vs2015

https://marketplace.visualstudio.com/items?itemName=ms-toolsai.vstoolsai-vs2017

https://docs.microsoft.com/en-us/cognitive-toolkit/setup-cntk-on-your-machine

https://www.microsoft.com/en-us/cognitive-toolkit/features/model-gallery/

https://github.com/Microsoft/CNTK

https://github.com/migueldeicaza/TensorFlowSharp

http://www.csharpkit.com/2017-10-15_55288.html

https://github.com/Microsoft/vs-tools-for-ai

作者：readilen

链接：https://www.jianshu.com/p/f678372b0444

來源：简书

简书著作权归作者所有，任何形式的转载都请联系作者获得授权并注明出处。