|Citation:||Chen C, Wang HF, Zhu QQ et al. Graph enhanced transformer for aspect category detection. JOURNAL OFCOMPUTER SCIENCE AND TECHNOLOGY 38(3): 612−625 May 2023. DOI: 10.1007/s11390-021-1000-1|
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.