Aspect Based Sentiment Analysis, PyTorch Implementations. 基于方面的情感分析,使用PyTorch实现。
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Updated
Jun 12, 2023 - Python
Aspect Based Sentiment Analysis, PyTorch Implementations. 基于方面的情感分析,使用PyTorch实现。
💭 Aspect-Based-Sentiment-Analysis: Transformer & Explainable ML (TensorFlow)
[EMNLP 2019 Workshop] Exploiting BERT for End-to-End Aspect-based Sentiment Analysis
AI Challenger 2018 细粒度用户评论情感分析,排名17th,基于Aspect Level 思路的解决方案
[AAAI 2019] A Unified Model for Opinion Target Extraction and Target Sentiment Prediction
A Multi-Aspect Multi-Sentiment Dataset for aspect-based sentiment analysis.
The datasets and code of ACL 2021 paper "Aspect-Category-Opinion-Sentiment Quadruple Extraction with Implicit Aspects and Opinions".
codes for paper A Multi-task Learning Model for Chinese-oriented Aspect Polarity Classification and Aspect Term Extraction
Aspect extraction from product reviews - window-CNN+maxpool+CRF, BiLSTM+CRF, MLP+CRF
Code and dataset for ACL2018 paper "Exploiting Document Knowledge for Aspect-level Sentiment Classification"
Aspect-Based Sentiment Analysis Experiments
CNN-based model to realize aspect extraction of restaurant reviews based on pre-trained word embeddings and part-of-speech tagging
A TensorFlow implementation for "Interactive Attention Networks for Aspect-Level Sentiment Classification"
Code and dataset for ACL2019 ‘‘An Interactive Multi-Task Learning Network for End-to-End Aspect-Based Sentiment Analysis’’.
Code and models for the paper " Position-Aware Tagging for Aspect Sentiment Triplet Extraction", EMNLP 2020.
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.
cat🐈: the repo for the paper "Embarrassingly Simple Unsupervised Aspect extraction"
Aspect-Sentiment-Opinion Triplet Extraction (ASOTE)
A TensorFlow implementation for "Recurrent Attention Network on Memory for Aspect Sentiment Analysis"
Transferable End-to-End Aspect-based Sentiment Analysis with Selective Adversarial Learning (EMNLP'19)
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