Syntactic and semantic dual-enhanced bidirectional network for aspect sentiment triplet extraction
Author:
Funder
山东省社科计划项目
Publisher
Springer Science and Business Media LLC
Subject
Hardware and Architecture,Information Systems,Theoretical Computer Science,Software
Link
https://link.springer.com/content/pdf/10.1007/s11227-023-05573-w.pdf
Reference42 articles.
1. Peng H, Xu L, Bing L, Huang F, Lu W, Si L (2020) Knowing what, how and why: a near complete solution for aspect-based sentiment analysis. In: Proceedings Of The AAAI Conference On Artificial Intelligence, vol. 34, pp 8600–8607
2. Wu Z, Ying C, Zhao F, Fan Z, Dai X, Xia R (2020) Grid tagging scheme for aspect-oriented fine-grained opinion extraction. In: Findings of the association for computational linguistics: EMNLP 2020, pp. 2576–2585
3. Xu L, Li H, Lu W, Bing L (2020) Position-aware tagging for aspect sentiment triplet extraction. In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, pp 2339–2349
4. Zhang Y, Ding Q, Zhu Z, Liu P, Xie F (2022) Enhancing aspect and opinion terms semantic relation for aspect sentiment triplet extraction. J Intell Inform Syst 59(2):523–542
5. Chen S, Wang Y, Liu J, Wang Y (2021) Bidirectional machine reading comprehension for aspect sentiment triplet extraction. In: Proceedings Of The AAAI Conference On Artificial Intelligence, vol. 35, pp 12666–12674
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