Keras Implementation of Aspect based Sentiment Analysis
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Updated
Mar 15, 2020 - Python
Keras Implementation of Aspect based Sentiment Analysis
Aspect Based Sentiment Analysis is a special type of sentiment analysis. In an explicit aspect, opinion is expressed on a target(opinion target), this aspect-polarity extraction is known as ABSA.
Transferable End-to-End Aspect-based Sentiment Analysis with Selective Adversarial Learning (EMNLP'19)
基于ChatGPT的情感分析
[TKDE] Knowledge Graph Augmented Network Towards Multiview Representation Learning for Aspect-based Sentiment Analysis
[EMNLP 2020] Multi-Instance Multi-Label Learning Networks for Aspect-Category Sentiment Analysis
[NLPCC 2020] Sentence Constituent-Aware Aspect-Category Sentiment Analysis with Graph Attention Networks
FinABSA is a T5-Large model trained for Aspect-Based Sentiment Analysis specifically for financial domains.
In this work (Targeted) Aspect-Based Sentiment Analysis task is converted to a sentence-pair classification task and a pre-trained BERT model is fine-tuned on it.
Code and dataset for our paper "Replicate, Walk, and Stop on Syntax: an Effective Neural Network Model for Aspect-Level Sentiment Classification", AAAI2020
Codes for the IJCAI2022 paper: Inheriting the Wisdom of Predecessors: A Multiplex Cascade Framework for Unified Aspect-based Sentiment Analysis
This repository contains the source codes for the paper: "Aspect Sentiment Triplet Extraction using Reinforcement Learning" published at CIKM 2021.
FastNLP Implementation of several ABSA subtasks and models also can be found in https://gitee.com/ROGERDJQ/FastABSA.git.
Unified Instance and Knowledge Alignment Pretraining for Aspect-based Sentiment Analysis
Attention-based LSTM model with the Aspect information to solve financial opinion mining problem (WWW 2018 shared task1)
Implement deep memory network used for Aspect Level Sentiment Classification
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