Aspect Category Detection
11 papers with code • 4 benchmarks • 4 datasets
Aspect category detection (ACD) in sentiment analysis aims to identify the aspect categories mentioned in a sentence.
Benchmarks
These leaderboards are used to track progress in Aspect Category Detection
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SemEval-2014 Task-4
FABSA
Most implemented papers
An Unsupervised Approach for Aspect Category Detection Using Soft Cosine Similarity Measure
Besides, most of these supervised methods require feature engineering to perform well.
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.
Cross-domain Aspect Category Transfer and Detection via Traceable Heterogeneous Graph Representation Learning
Aspect category detection is an essential task for sentiment analysis and opinion mining.
Leveraging Just a Few Keywords for Fine-Grained Aspect Detection Through Weakly Supervised Co-Training
gkaramanolakis/ISWD
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IJCNLP 2019
In this work, we consider weakly supervised approaches for training aspect classifiers that only require the user to provide a small set of seed words (i. e., weakly positive indicators) for the aspects of interest.
Embarrassingly Simple Unsupervised Aspect Extraction
We present a simple but effective method for aspect identification in sentiment analysis.
Sentence Constituent-Aware Aspect-Category Sentiment Analysis with Graph Attention Networks
l294265421/SCAN
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Aspect category sentiment analysis (ACSA) aims to predict the sentiment polarities of the aspect categories discussed in sentences.
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.
Latent Aspect Detection from Online Unsolicited Customer Reviews
Within the context of review analytics, aspects are the features of products and services at which customers target their opinions and sentiments.
Label-Driven Denoising Framework for Multi-Label Few-Shot Aspect Category Detection
1429904852/ldf
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Multi-Label Few-Shot Aspect Category Detection (FS-ACD) is a new sub-task of aspect-based sentiment analysis, which aims to detect aspect categories accurately with limited training instances.
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.
