A dual contrastive learning-based graph convolutional network with syntax label enhancement for aspect-based sentiment classification

A dual contrastive learning-based graph convolutional network with syntax label enhancement for aspect-based sentiment classification

Introduction: Aspect-based sentiment classification is a fine-grained sentiment classification task. State-of-the-art approaches in this field leverage graph neural networks to integrate sentence syntax dependency. However, current methods fail to exploit the data augmentation in encoding and ignore...

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Bibliographic Details
Main Authors: Yuyan Huang, Anan Dai, Sha Cao, Qiuhua Kuang, Hongya Zhao, Qianhua Cai
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-04-01
Series:Frontiers in Physics
Subjects:
aspect-based sentiment classification
graph convolutional networks
dual contrastive learning
syntax label enhancement
bidirectional encoder representations from transformers (BERT)
Online Access:https://www.frontiersin.org/articles/10.3389/fphy.2024.1336795/full

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https://www.frontiersin.org/articles/10.3389/fphy.2024.1336795/full

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