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Neural transition model for aspect-based sentiment triplet extraction with triplet memory

Neurocomputing, 2021
Abstract The aspect-based sentiment triplet extraction (ASTE), as a complete sentiment analysis task, aims to recognize the aspect term, the opinion expression, and the sentiment polarity in a sentence. Current state-of-the-art ASTE models employ a joint extracting scheme for better task improvements.
Shengqiong Wu   +4 more
exaly   +2 more sources

Double embedding and bidirectional sentiment dependence detector for aspect sentiment triplet extraction

Knowledge-Based Systems, 2022
Dawei Dai   +4 more
exaly   +2 more sources

Exploiting Duality in Aspect Sentiment Triplet Extraction With Sequential Prompting

IEEE Transactions on Knowledge and Data Engineering
Jingping Liu, Chao Wang, Haiyun Jiang
exaly   +2 more sources

Hierarchical Sequence Labeling Model for Aspect Sentiment Triplet Extraction

2020
Aspect sentiment triplet extraction is an emerging task in aspect-based sentiment analysis, which aims at simultaneously identifying the aspect, the opinion expression, and the sentiment from a given review sentence. Existing studies divide this task into many sub-tasks and process them in a pipeline manner, which ignores the relevance between ...
Peng Chen, Shaowei Chen, Jie Liu 0007
openaire   +1 more source

Span-based syntactic feature fusion for aspect sentiment triplet extraction

Information Fusion
Guangtao Xu   +4 more
exaly   +2 more sources

Dual-Channel Span for Aspect Sentiment Triplet Extraction

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023
Pan Li, Ping Li, Kai Zhang
openaire   +1 more source

Document-Level Sentiment Knowledge Transfer Network for Aspect Sentiment Triplet Extraction

2022 IEEE 34th International Conference on Tools with Artificial Intelligence (ICTAI), 2022
Long Tan, Zixian Su
openaire   +1 more source

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