chenhaihua's repositories
anystyle-parser
fast and smart citation reference parsing
attribute_charge
The source code of our COLING'18 paper "Few-Shot Charge Prediction with Discriminative Legal Attributes".
DecodingLaw
Deep learning for legal domain
DeepLearning-500-questions
深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系scutjy2015@163.com 版权所有，违权必究 Tan 2018.06
legal-ner
Named entity recognition for the legal domain
legal-text-mining
Experiments classifying legal documents into their sub-categories: e.g. civil law, criminal law or administrative law. Classifiers used: k-Nearest Neighbours linear Support Vector Machine Random Forest Convolutional Neural Network Long Short Term Memory Neural Network
Legal_Judgment_Prediction_BiLSTM_ATT
Legal Juegment Prediction (LJP) with BiLSTM and Attention
LegalKGSEU
法律知识图谱网站。A legal knowledge graph web project.
LegalSearch
Legal text search engine that uses semantic search algorithm in order to find related keywords and sort the results by relevance.
LeGloVe
Legal domain-specific word vectors, trained with GloVe on a corpus of legal documents.
lexpredict-lexnlp
LexNLP by LexPredict
parse_legalfile
解析中文裁判文书
summarization
Implementation of different summarization algorithms applied to legal case judgements.
t81_558_deep_learning
Washington University (in St. Louis) Course T81-558: Applications of Deep Neural Networks
text-analytics-with-python
Learn how to process, classify, cluster, summarize, understand syntax, semantics and sentiment of text data with the power of Python! This repository contains code and datasets used in my book, "Text Analytics with Python" published by Apress/Springer.
unt_hpc
This repo is designed for the University of North Texas (UNT) High Performance Computing (HPC) - Data Science & Analytics (DSA). It containes short tutorials, code snippets and notebooks and other info on how to use the UNT supercomputer for data science.
word2vec
Automatically exported from code.google.com/p/word2vec