NLPChina ORG

Use SQL to query Elasticsearch

ansj分词.ict的真正java实现.分词效果速度都超过开源版的ict. 中文分词,人名识别,词性标注,用户自定义词典

这个项目是一个基本包.封装了大多数nlp项目中常用工具

word2vec java版本的一个实现

No description.

A curated list of resources for NLP (Natural Language Processing) for Chinese 中文自然语言处理相关资料

Java Dynamic code or JAR , publish you Api or Schedule in flying

A Chinese Words Segmentation Tool Based on Bayes Model

LDA 的java实现

nutz+jetty+h2 做的一个web应用

🥇掘金翻译计划，可能是世界最大最好的英译中技术社区，最懂读者和译者的翻译平台：

Jcoder & Elasticsearch sites

新浪微博模拟登陆2014-04-01版

ansj_parsing 依存文法&句法分析

天亮分词器第12个小版本

Scikit-Learn, NLTK, Spacy, Gensim, Textblob and more

PyNLPl, pronounced as 'pineapple', is a Python library for Natural Language Processing. It contains various modules useful for common, and less common, NLP tasks. PyNLPl can be used for basic tasks such as the extraction of n-grams and frequency lists, and to build simple language model. There are also more complex data types and algorithms. Moreover, there are parsers for file formats common in NLP (e.g. FoLiA/Giza/Moses/ARPA/Timbl/CQL). There are also clients to interface with various NLP specific servers. PyNLPl most notably features a very extensive library for working with FoLiA XML (Format for Linguistic Annotation).

A Package of Keyphrase Extraction and Social Tag Suggestion

基于TextRank和WordNet的中英文单文档自动摘要

LAnguage Representations Kit

Data loaders and abstractions for text and NLP

a structured data system on top of ChubaoFS

Tensors and Dynamic neural networks in Python with strong GPU acceleration

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

Evaluating Cross-lingual Sentence Representations

Just the facts -- web page content extraction

Training/test data for Dragnet

fast python port of arc90's readability tool, updated to match latest readability.js!

Information Extraction in Python

MITIE: library and tools for information extraction

A toolkit for coreference resolution and error analysis.

Neural Coref Models