GitHub topics: aspect-term-extraction
yangheng95/PyABSA
Sentiment Analysis, Text Classification, Text Augmentation, Text Adversarial defense, etc.;
Language: Jupyter Notebook - Size: 37.1 MB - Last synced at: 4 days ago - Pushed at: 4 days ago - Stars: 994 - Forks: 166
lixin4ever/E2E-TBSA
[AAAI 2019] A Unified Model for Opinion Target Extraction and Target Sentiment Prediction
Language: Python - Size: 2.21 MB - Last synced at: 15 days ago - Pushed at: over 1 year ago - Stars: 273 - Forks: 59
declare-lab/ASTE-RL
This repository contains the source codes for the paper: "Aspect Sentiment Triplet Extraction using Reinforcement Learning" published at CIKM 2021.
Language: Python - Size: 39.1 KB - Last synced at: 9 days ago - Pushed at: about 2 years ago - Stars: 19 - Forks: 3
lixin4ever/HAST
Aspect Term Extraction with History Attention and Selective Transformation (IJCAI 2018)
Language: Python - Size: 1.28 MB - Last synced at: 13 days ago - Pushed at: almost 6 years ago - Stars: 54 - Forks: 10
abhishek21441/NLP-Assignments
Assignments of the course CSE 556 - Natural Language Processing
Language: Jupyter Notebook - Size: 22.2 MB - Last synced at: 9 months ago - Pushed at: 9 months ago - Stars: 0 - Forks: 0
kevinscaria/InstructABSA
Instructional learning for Aspect Based Sentiment Analysis
Language: Jupyter Notebook - Size: 1.61 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 96 - Forks: 16
yangheng95/LCF-ATEPC
codes for paper A Multi-task Learning Model for Chinese-oriented Aspect Polarity Classification and Aspect Term Extraction
Language: Python - Size: 2.43 MB - Last synced at: over 1 year ago - Pushed at: almost 3 years ago - Stars: 181 - Forks: 42
ChocoWu/Synfue-PAOTE
Source code for IJCAI 2021 paper: Learn from Syntax: Improving Pair-wise Aspect and Opinion Terms Extraction with Rich Syntactic Knowledge
Language: Python - Size: 1.19 MB - Last synced at: over 1 year ago - Pushed at: over 2 years ago - Stars: 16 - Forks: 3
nicolezattarin/BERT-Aspect-Based-Sentiment-Analysis
Class for Aspect-term extraction and Aspect-based sentiment analysis with BERT and Adapters
Language: Jupyter Notebook - Size: 6.3 MB - Last synced at: almost 2 years ago - Pushed at: almost 3 years ago - Stars: 14 - Forks: 0
ArrowLuo/DOER
The implementation of ACL 2019 paper DOER: Dual Cross-Shared RNN for Aspect Term-Polarity Co-Extraction
Language: Python - Size: 34.1 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 59 - Forks: 6
trtm/ABAM 📦
Accompanying repository of our 7th Workshop on Argument Mining (2020) paper "Aspect-Based Argument Mining"
Language: Python - Size: 385 KB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 4 - Forks: 1
1tangerine1day/Aspect-Term-Extraction-and-Analysis
Aspect Term Extraction and Aspect-based Sentiment Analysis on SemEval-2014 task4
Language: Jupyter Notebook - Size: 1.03 MB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 21 - Forks: 11
ArrowLuo/GRACE
The impletation of paper titled GRACE: Gradient Harmonized and Cascaded Labeling for Aspect-based Sentiment Analysis
Language: Python - Size: 1.03 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 17 - Forks: 8
ArrowLuo/BiDTree
The implementation of TASLP 2019 paper Improving Aspect Term Extraction with Bidirectional Dependency Tree Representation
Language: Python - Size: 12.4 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 9 - Forks: 4
SalvatoreCognetta/NLP-AspectTermExtraction
NLP: aspect term extraction and sentiment polarity using Bert Transformer with pytorch and pytorch-lightning.
Language: Jupyter Notebook - Size: 4.26 MB - Last synced at: about 2 years ago - Pushed at: over 3 years ago - Stars: 0 - Forks: 0
Shikhar-S/Multi-Aspect-Sentiment-Classification-for-Online-Medical-Reviews
Implementation of Document Level Multi Aspect Sentiment Classification for Online Reviews of Medical Experts
Language: Jupyter Notebook - Size: 267 MB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 2 - Forks: 0
