Aspect Sentiment Triplet Extraction with Syntax-Semantics Graph Convolutional Network [PDF]
International Journal of Computational Intelligence SystemsIn the traditional task of aspect sentiment triplet extraction, existing approaches typically focus on either syntactic or semantic features independently, failing to leverage the complementary integration of these two types of information.
Jingyun Zhang +3 more
doaj +3 more sources
A semantically enhanced dual encoder for aspect sentiment triplet extraction [PDF]
Neurocomputing, 2023 Aspect sentiment triplet extraction (ASTE) is a crucial subtask of aspect-based sentiment analysis (ABSA) that aims to comprehensively identify sentiment triplets. Previous research has focused on enhancing ASTE through innovative table-filling strategies.
Baoxing Jiang, Dingge Liang
exaly +4 more sources
Structural Bias for Aspect Sentiment Triplet Extraction
CoRR, 2022 Structural bias has recently been exploited for aspect sentiment triplet extraction (ASTE) and led to improved performance. On the other hand, it is recognized that explicitly incorporating structural bias would have a negative impact on efficiency ...
Ma, Fang +5 more
core +3 more sources
CONTRASTE: Supervised Contrastive Pre-training With Aspect-based Prompts For Aspect Sentiment Triplet Extraction [PDF]
, 2023 Existing works on Aspect Sentiment Triplet Extraction (ASTE) explicitly focus on developing more efficient fine-tuning techniques for the task. Instead, our motivation is to come up with a generic approach that can improve the downstream performances of ...
Goyal, Pawan +3 more
core +4 more sources
Dual Encoder: Exploiting the Potential of Syntactic and Semantic for Aspect Sentiment Triplet Extraction [PDF]
Aspect Sentiment Triple Extraction (ASTE) is an emerging task in fine-grained sentiment analysis. Recent studies have employed Graph Neural Networks (GNN) to model the syntax-semantic relationships inherent in triplet elements.
Xu, Xiujuan, Zhao, Xiaowei, Zhou, Yong
core +2 more sources
Multi-feature Interaction for Aspect Sentiment Triplet Extraction [PDF]
Jisuanji kexue yu tansuoAspect sentiment triple extraction is one of the subtasks of aspect-level sentiment analysis, which aims to extract aspect terms, corresponding opinion terms and sentiment polarity in sentence.
CHEN Linying, LIU Jianhua, ZHENG Zhixiong, LIN Jie, XU Ge, SUN Shuihua
doaj +2 more sources
A Robustly Optimized BMRC for Aspect Sentiment Triplet Extraction [PDF]
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022 Shu Liu, Kaiwen Li, Zuhe Li
openalex +2 more sources
FOAL: Fine-grained Contrastive Learning for Cross-domain Aspect Sentiment Triplet Extraction [PDF]
, 2023 Aspect Sentiment Triplet Extraction (ASTE) has achieved promising results while relying on sufficient annotation data in a specific domain. However, it is infeasible to annotate data for each individual domain.
Dai, Xinyu +3 more
core +2 more sources
Learning Span-Level Interactions for Aspect Sentiment Triplet Extraction [PDF]
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), 2021 ACL 2021, long paper, main ...
Lu Xu, Yew Ken Chia, Lidong Bing
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Semantic and Syntactic Enhanced Aspect Sentiment Triplet Extraction [PDF]
Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, 2021 Aspect Sentiment Triplet Extraction (ASTE) aims to extract triplets from sentences, where each triplet includes an entity, its associated sentiment, and the opinion span explaining the reason for the sentiment.Most existing research addresses this problem in a multi-stage pipeline manner, which neglects the mutual information between such three ...
Zhexue Chen +4 more
+6 more sources