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PyTorch implementation of 'An Unsupervised Neural Attention Model for Aspect Extraction' by He et al. ACL2017'

Enhanced Multi-Channel Graph Convolutional Network for Aspect Sentiment Triplet Extraction

Auto labeling-tool implemented with PyTorch for aspect-based sentiment analysis.

Code and models for the paper " Position-Aware Tagging for Aspect Sentiment Triplet Extraction", EMNLP 2020.

Coupled Multi-Layer Attentions for Co-Extraction of Aspect and Opinion Terms

Aspect Sentiment Triplet Extraction (ASTE) dataset in AAAI 2020, EMNLP 2020 and ACL 2021.

Code and data for paper "Grid Tagging Scheme for Aspect-oriented Fine-grained Opinion Extraction". Aspect opinion pair datasets and aspect triplet datasets.

Code Implementation of "Learning Span-Level Interactions for Aspect Sentiment Triplet Extraction".

Code and dataset for EMNLP 2020 paper titled "A Multi-task Learning Framework for Opinion Triplet Extraction"

The datasets and code of ACL 2021 paper "Aspect-Category-Opinion-Sentiment Quadruple Extraction with Implicit Aspects and Opinions".

Aspect Term Extraction and Aspect-based Sentiment Analysis on SemEval-2014 task4

codes for paper A Multi-task Learning Model for Chinese-oriented Aspect Polarity Classification and Aspect Term Extraction

Aspect-Sentiment-Opinion Triplet Extraction (ASOTE)

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.

Code for unsupervised aspect extraction, using Keras and its Backends

CNN-based model to realize aspect extraction of restaurant reviews based on pre-trained word embeddings and part-of-speech tagging

Aspect extraction from product reviews - window-CNN+maxpool+CRF, BiLSTM+CRF, MLP+CRF

Code for acl2017 paper "An unsupervised neural attention model for aspect extraction"