Enhance Cross-Domain Aspect-Based Sentiment Analysis by Incorporating Commonsense Relational Structure (Student Abstract)

Authors

  • Yushi Zeng South China University of Technology
  • Guohua Wang South China University of Technology
  • Haopeng Ren South China University of Technology
  • Yi Cai South China University of Technology

DOI:

https://doi.org/10.1609/aaai.v36i11.21689

Keywords:

Cross-Domain, Aspect Based Sentiment Analysis, Knowledge Graph

Abstract

Aspect Based Sentiment Analysis (ABSA) aims to extract aspect terms and identify the sentiment polarities towards each extracted aspect term. Currently, syntactic information is seen as the bridge for the domain adaptation and achieves remarkable performance. However, the transferable syntactic knowledge is complex and diverse, which causes the transfer error problem in domain adaptation. In our paper, we propose a domain-shared relational structure incorporated cross-domain ABSA model. The experimental results show the effectiveness of our model.

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Published

2022-06-28

How to Cite

Zeng, Y., Wang, G., Ren, H., & Cai, Y. (2022). Enhance Cross-Domain Aspect-Based Sentiment Analysis by Incorporating Commonsense Relational Structure (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence, 36(11), 13105-13106. https://doi.org/10.1609/aaai.v36i11.21689