Boundary-Driven Table-Filling for Aspect Sentiment Triplet Extraction
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022 Aspect Sentiment Triplet Extraction (ASTE) aims to extract the aspect terms along with the corresponding opinion terms and the expressed sentiments in the review, which is an important task in sentiment analysis.
Yice Zhang +7 more
openaire +2 more sources
Measuring Your ASTE Models in The Wild: A Diversified Multi-domain Dataset For Aspect Sentiment Triplet Extraction [PDF]
, 2023 Aspect Sentiment Triplet Extraction (ASTE) is widely used in various applications. However, existing ASTE datasets are limited in their ability to represent real-world scenarios, hindering the advancement of research in this area.
Ting Xu +5 more
core +5 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.
Baoxing Jiang +4 more
semanticscholar +3 more sources
PASTE: A Tagging-Free Decoding Framework Using Pointer Networks for Aspect Sentiment Triplet Extraction [PDF]
Conference on Empirical Methods in Natural Language Processing, 2021 Aspect Sentiment Triplet Extraction (ASTE) deals with extracting opinion triplets, consisting of an opinion target or aspect, its associated sentiment, and the corresponding opinion term/span explaining the rationale behind the sentiment.
Rajdeep Mukherjee +4 more
semanticscholar +5 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
Explicit Interaction Network for Aspect Sentiment Triplet Extraction [PDF]
, 2021 Aspect Sentiment Triplet Extraction (ASTE) aims to recognize targets, their sentiment polarities and opinions explaining the sentiment from a sentence. ASTE could be naturally divided into 3 atom subtasks, namely target detection, opinion detection and sentiment classification.
Wang, Peiyi +5 more
openaire +3 more sources
Integration of Multi-Branch GCNs Enhancing Aspect Sentiment Triplet Extraction
Applied Sciences, 2023 Aspect Sentiment Triplet Extraction (ASTE) is a complex and challenging task in Natural Language Processing (NLP). It aims to extract the triplet of aspect term, opinion term, and their associated sentiment polarity, which is a more fine-grained study in
Xuefeng Shi +5 more
doaj +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.
Ting Xu +3 more
openalex +3 more sources
IDCN: A Novel Interactive Dual Channel Network for Aspect Sentiment Triplet Extraction [PDF]
IEEE Access, 2022 Aspect sentiment triplet extraction (ASTE) is one of the important subtasks of aspect-based sentiment analysis, it aims at detecting the aspect terms, opinion terms, and the corresponding sentiment polarity, simultaneously.
Ning Liu +4 more
doaj +2 more sources
Affective Commonsense Knowledge Enhanced Dependency Graph for aspect sentiment triplet extraction [PDF]
The Journal of Supercomputing, 2023 Abstract Most existing aspect sentiment triplet extraction models emphasize the adoption of novel tagging scheme to jointly extract three elements of sentiment triplets, but they overlook the intrinsic information of individual words, including the implicit relationships between words, which results in the inaccurate triplet extraction. In this
Xiaowen Sun +4 more
openaire +2 more sources