Aspect Category Polarity
5 papers with code • 1 benchmarks • 3 datasets
AWARE
FABSA
Most implemented papers
A Deep Convolutional Neural Networks Based Multi-Task Ensemble Model for Aspect and Polarity Classification in Persian Reviews
The results indicate that this new approach increases the efficiency of the sentiment analysis model in the Persian language.
Jointly Modeling Aspect and Polarity for Aspect-based Sentiment Analysis in Persian Reviews
The developed models were evaluated using the collected dataset in terms of example-based and label-based metrics.
MvP: Multi-view Prompting Improves Aspect Sentiment Tuple Prediction
ZubinGou/multi-view-prompting
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Generative methods greatly promote aspect-based sentiment analysis via generating a sequence of sentiment elements in a specified format.
Deep Learning Brasil at ABSAPT 2022: Portuguese Transformer Ensemble Approaches
ju-resplande/dlb_absapt2022
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Aspect-based Sentiment Analysis (ABSA) is a task whose objective is to classify the individual sentiment polarity of all entities, called aspects, in a sentence.
FABSA: An aspect-based sentiment analysis dataset of user reviews
The majority of available ABSA systems heavily rely on manually annotated datasets to train supervised machine learning models.
