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Graph Enhanced Transformer for Aspect Category Detection
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Journal Article
Graph Enhanced Transformer for Aspect Category Detection
2023
Overview
Aspect category detection is one challenging subtask of aspect based sentiment analysis, which categorizes a review sentence into a set of predefined aspect categories. Most existing methods regard the aspect category detection as a flat classification problem. However, aspect categories are inter-related, and they are usually organized with a hierarchical tree structure. To leverage the structure information, this paper proposes a hierarchical multi-label classification model to detect aspect categories and uses a graph enhanced transformer network to integrate label dependency information into prediction features. Experiments have been conducted on four widely-used benchmark datasets, showing that the proposed model outperforms all strong baselines.
Publisher
Springer Nature Singapore,Springer,Springer Nature B.V
