Aspect-level sentiment classification with aspect-opinion sentence pattern connection graph convolutional networks-Reference-Cited by-同舟云学术

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Aspect-level sentiment classification with aspect-opinion sentence pattern connection graph convolutional networks

Published:2024-04-11 Issue:11 Volume:80 Page:16474-16496
ISSN:0920-8542
Container-title:The Journal of Supercomputing
language:en
Short-container-title:J Supercomput

Author:

Li Hongye,Xu Fuyong,Zhang Zhiyu,Liu Peiyu,Zhang Wenyin

Funder

Key R & D project of Shandong Province

Shandong Provincial Social Science Planning Project

National Science Foundation of China

Natural Science Foundation of Shandong Province

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s11227-024-06093-x.pdf

Reference45 articles.

1. Chen C, Teng Z, Zhang Y (2020) Inducing target-specific latent structures for aspect sentiment classification. In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 5596–5607

2. Jiang B, Xu G, Liu P (2023) Aspect-level sentiment classification via location enhanced aspect-merged graph convolutional networks. J Supercomput 79(9):9666

3. Li X, Bing L, Lam W, Shi B (2018) Transformation networks for target-oriented sentiment classification. arXiv preprint arXiv:1805.01086

4. Song Y, Wang J, Jiang T, Liu Z, Rao Y (2019) Attentional encoder network for targeted sentiment classification. arXiv preprint arXiv:1902.09314

5. Wang Y, Huang M, Zhu X, Zhao, L (2016) Attention-based lstm for aspect-level sentiment classification. In: Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, pp 606–615

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