Relevance-aware visual entity filter network for multimodal aspect-based sentiment analysis-Reference-Cited by-同舟云学术

Relevance-aware visual entity filter network for multimodal aspect-based sentiment analysis

Published:2024-08-30 Issue: Volume: Page:
ISSN:1868-8071
Container-title:International Journal of Machine Learning and Cybernetics
language:en
Short-container-title:Int. J. Mach. Learn. & Cyber.

Author:

Chen Yifan,Xiong Haoliang,Li Kuntao,Mai Weixing,Xue Yun,Cai Qianhua,Li Fenghuan

Funder

Guangdong Basic and Applied Basic Research Foundation

National Natural Science Foundation of China

Characteristic Innovation Projects of Guangdong Colleges and Universities

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s13042-024-02342-w.pdf

Reference39 articles.

1. Zhang W, Li X, Deng Y, Bing L, Lam W (2022) A survey on aspect-based sentiment analysis: tasks, methods, and challenges. IEEE Trans Knowl Data Eng 01:1–20

2. Jiang L, Zou Z, Liao J, Li Y (2023) A study on the application of sentiment-support words on aspect-based sentiment analysis. Int J Pattern Recognit Artif Intell 37(07):2357004

3. Jiang L, Li Y, Liao J, Zou Z, Jiang C (2023) Research on non-dependent aspect-level sentiment analysis. Knowl-Based Syst 266:110419

4. Zhang Z, Zhou Z, Wang Y (2022) Ssegcn: syntactic and semantic enhanced graph convolutional network for aspect-based sentiment analysis. In: Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp 4916–4925

5. Zhang M, Zhu Y, Liu Z, Bao Z, Wu Y, Sun X, Xu L (2023) Span-level aspect-based sentiment analysis via table filling. In: Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp 9273–9284