Automatic Verbalizer for Extracting Fine-Grained Customer Opinions from Non-English Social Media Comments-Reference-Cited by-同舟云学术

Automatic Verbalizer for Extracting Fine-Grained Customer Opinions from Non-English Social Media Comments

Published:2024 Issue: Volume: Page:23-32
ISSN:1865-0929
Container-title:Communications in Computer and Information Science
language:en
Short-container-title:

Author:

Chu Carlin C. F.^ORCID,Leung Jonathan H. Y.^ORCID,So Raymond^ORCID,Chan Andy^ORCID

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-61966-3_3

Reference17 articles.

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3. Cai, H., Tu, Y., Zhou, X., Yu, J., Xia, R.: Aspect-category based sentiment analysis with hierarchical graph convolutional network. In: Proceedings of the 28th International Conference on Computational Linguistics, pp. 833–843. International Committee on Computational Linguistics, Barcelona (2020). https://doi.org/10.18653/v1/2020.coling-main.72

4. Cui, G., Hu, S., Ding, N., Huang, L., Liu, Z.: Prototypical verbalizer for prompt-based few-shot tuning. In: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics, vol. 1: Long Papers, pp. 7014–7024. Association for Computational Linguistics, Dublin (2022). https://doi.org/10.18653/v1/2022.acl-long.483

5. Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, vol. 1 (Long and Short Papers). pp. 4171–4186. Association for Computational Linguistics, Minneapolis (2019). https://doi.org/10.18653/v1/N19-1423