Pinned Repositories
Aspect-Based-Sentiment-Analysis
Aspect-Based Sentiment Analysis Experiments
Bidirectional-LSTM-CRF-for-Clinical-Concept-Extraction
Bidirectional LSTM-CRF for Clinical Concept Extraction using i2b2-2010 data
comparative-sentences-mining
Automatically exported from code.google.com/p/comparative-sentences-mining
ComparativeSentencesExtraction
csr
规则方法联合机器学习方法
EVNUM
Matlab experiments of the Electric Vehicle charging Network Utility Maximization
FineGrainedOpinionMining
细粒度情感分析repository2：细粒度情感分析接口，aspect-based sentiment analysis based on HMM.
iep-miner
A java implementation of a comparable entitity miner
mem_absa
Aspect Based Sentiment Analysis using End-to-End Memory Networks
WaiMaiOpinionMiner
细粒度情感分析repository1：Wai Mai Opinion Miner，细粒度情感分析系统GUI demo。
Cherryjky's Repositories
Cherryjky/FineGrainedOpinionMining
细粒度情感分析repository2：细粒度情感分析接口，aspect-based sentiment analysis based on HMM.
Cherryjky/mem_absa
Aspect Based Sentiment Analysis using End-to-End Memory Networks
Cherryjky/WaiMaiOpinionMiner
细粒度情感分析repository1：Wai Mai Opinion Miner，细粒度情感分析系统GUI demo。
Cherryjky/Aspect-Based-Sentiment-Analysis
Aspect-Based Sentiment Analysis Experiments
Cherryjky/Bidirectional-LSTM-CRF-for-Clinical-Concept-Extraction
Bidirectional LSTM-CRF for Clinical Concept Extraction using i2b2-2010 data
Cherryjky/comparative-sentences-mining
Automatically exported from code.google.com/p/comparative-sentences-mining
Cherryjky/ComparativeSentencesExtraction
Cherryjky/csr
规则方法联合机器学习方法
Cherryjky/EVNUM
Matlab experiments of the Electric Vehicle charging Network Utility Maximization
Cherryjky/iep-miner
A java implementation of a comparable entitity miner
Cherryjky/jieba
结巴中文分词
Cherryjky/MachineLearning
一些关于机器学习的学习资料与研究介绍
Cherryjky/NamedEntity_realtion_extraction
基于句法分析的命名实体关系抽取程序
Cherryjky/NLPIR
Cherryjky/nltk
NLTK Source
Cherryjky/PrefixSpan-py
The shortest yet efficient implementation of famous frequent sequence mining algorithm PrefixSpan in Python.
Cherryjky/relation-extraction
entity relation project for Information Extraction, Sping 2014
Cherryjky/sentiment
Classify the sentiment of sentences from the Rotten Tomatoes dataset "There's a thin line between likably old-fashioned and fuddy-duddy, and The Count of Monte Cristo ... never quite settles on either side." The Rotten Tomatoes movie review dataset is a corpus of movie reviews used for sentiment analysis, originally collected by Pang and Lee. In their work on sentiment treebanks, Socher et al. used Amazon's Mechanical Turk to create fine-grained labels for all parsed phrases in the corpus. This project presents a chance to benchmark your sentiment-analysis ideas on the Rotten Tomatoes dataset. We have to label phrases on a scale of five values: negative, somewhat negative, neutral, somewhat positive, positive. Obstacles like sentence negation, sarcasm, terseness, language ambiguity, and many others make this task very challenging.
Cherryjky/sequential_classifiers
some classifying of sequences