Results 11 to 20 of about 4,141 (216)
Structural Bias for Aspect Sentiment Triplet Extraction [PDF]
, 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, whereas pretrained language models (PLMs) can already capture implicit structures.
Zhang, Chen +5 more
core +4 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 Aspect sentiment triplet extraction (ASTE) is a challenging subtask in aspect-based sentiment analysis. It aims to explore the triplets of aspects, opinions and sentiments with complex correspondence from the context.
Shu Liu, Kaiwen Li, Zuhe Li
semanticscholar +3 more sources
A Span-level Bidirectional Network for Aspect Sentiment Triplet Extraction [PDF]
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022 Aspect Sentiment Triplet Extraction (ASTE) is a new fine-grained sentiment analysis task that aims to extract triplets of aspect terms, sentiments, and opinion terms from review sentences. Recently, span-level models achieve gratifying results on ASTE task by taking advantage of the predictions of all possible spans.
Chen, Yuqi +3 more
semanticscholar +7 more sources
Span-Level Dual-Encoder Model for Aspect Sentiment Triplet Extraction [PDF]
Jisuanji kexue yu tansuo, 2023 Aspect sentiment triplet extraction (ASTE) is one of the subtasks of aspect-based sentiment analysis, which aims to identify all aspect terms, their corresponding opinion terms and sentiment polarities in sentences.
ZHANG Yunqi, LI Songda, LAN Yuquan, LI Dongxu, ZHAO Hui
doaj +4 more sources
ASTE-Transformer: Modelling Dependencies in Aspect-Sentiment Triplet Extraction [PDF]
Findings of the Association for Computational Linguistics: EMNLP 2024Aspect-Sentiment Triplet Extraction (ASTE) is a recently proposed task of aspect-based sentiment analysis that consists in extracting (aspect phrase, opinion phrase, sentiment polarity) triples from a given sentence. Recent state-of-the-art methods approach this task by first extracting all possible text spans from a given text, then filtering the ...
Naglik, Iwo, Lango, Mateusz
semanticscholar +6 more sources
A Pairing Enhancement Approach for Aspect Sentiment Triplet Extraction [PDF]
, 2023 Aspect Sentiment Triplet Extraction (ASTE) aims to extract the triplet of an aspect term, an opinion term, and their corresponding sentiment polarity from the review texts. Due to the complexity of language and the existence of multiple aspect terms and opinion terms in a single sentence, current models often confuse the connections between an aspect ...
Yang, Fan +3 more
core +4 more sources
Part-of-speech based label update network for aspect sentiment triplet extraction
Journal of King Saud University: Computer and Information SciencesAspect sentiment triplet analysis (ASTE) is a nuanced task that entails the extraction of all triplets from a user comment, where each triplet consist of an aspect term, an opinion term, and the associated sentiment polarity of the aspect term.
Yanbo Li, Qing He, Liu Yang
doaj +3 more sources
STAGE: Span Tagging and Greedy Inference Scheme for Aspect Sentiment Triplet Extraction [PDF]
AAAI Conference on Artificial Intelligence, 2022 Aspect Sentiment Triplet Extraction (ASTE) has become an emerging task in sentiment analysis research, aiming to extract triplets of the aspect term, its corresponding opinion term, and its associated sentiment polarity from a given sentence.
Shuo Liang +5 more
semanticscholar +3 more sources
Enhanced Multi-Channel Graph Convolutional Network for Aspect Sentiment Triplet Extraction [PDF]
Annual Meeting of the Association for Computational Linguistics, 2022 Aspect Sentiment Triplet Extraction (ASTE) is an emerging sentiment analysis task. Most of the existing studies focus on devising a new tagging scheme that enables the model to extract the sentiment triplets in an end-to-end fashion.
Hao Chen +4 more
semanticscholar +2 more sources
A Multi-Task Dual-Encoder Framework for Aspect Sentiment Triplet Extraction [PDF]
IEEE Access, 2022 Aspect Sentiment Triplet Extraction (ASTE) is a complex and important task in aspect-based sentiment analysis task, which aims to extract aspect-sentiment-opinion triplets from review sentences, to acquire comprehensive information for sentiment analysis.
Hai Huan +3 more
doaj +2 more sources