Results 161 to 170 of about 4,141 (216)

DiffuSyn: A Diffusion-Driven Framework With Syntactic Dependency for Aspect Sentiment Triplet Extraction

IEEE Transactions on Audio, Speech, and Language Processing
Aspect Sentiment Triplet Extraction (ASTE) is a fine-grained sentiment analysis task that involves identifying aspect and opinion terms and conducting sentiment analysis for each aspect-opinion pair.
Qiuhua Yi, Xiangjie Kong, Linan Zhu, Chenwei Zhang, Guojiang Shen   +4 more
semanticscholar   +1 more source

Aspect Sentiment Triplet Extraction: A Seq2Seq Approach With Span Copy Enhanced Dual Decoder

IEEE/ACM Transactions on Audio Speech and Language Processing, 2022
Aspect Sentiment Triplet Extraction (ASTE) is a relatively new and very challenging task that attempts to provide an integral solution for aspect-based sentiment analysis.
Zhihao Zhang, Y. Zuo, Junjie Wu
semanticscholar   +1 more source

Span-level bidirectional retention scheme for aspect sentiment triplet extraction

Information Processing & Management
Xuan Yang, Tao Peng, Haijia Bi, Jiayu Han   +3 more
openaire   +2 more sources

Template-Order Driven Feature Integration With Generative Models for Aspect Sentiment Triplet Extraction

IEEE Transactions on Audio, Speech, and Language Processing
Aspect-based sentiment analysis (ABSA), which explores the nuanced sentiments individuals express toward specific services or products, has shown significant potential in practical applications. Recently, the aspect sentiment triplet extraction field has
Jiazhou Chen, Ruiqiang Guo
semanticscholar   +1 more source

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
openaire   +1 more source

Mixture of Hybrid Prompts for Cross-Domain Aspect Sentiment Triplet Extraction

IEEE Transactions on Affective Computing
Cross-domain Aspect Sentiment Triplet Extraction (ASTE) aims to extract the triplets from the review of a target domain, utilizing knowledge from a source domain. As a newly proposed task, limited work has been devoted to it.
Fan Yang, Xiabing Zhou, Min Zhang, Guodong Zhou   +3 more
semanticscholar   +1 more source

Leveraging dependency and constituent graphs for aspect sentiment triplet extraction

Information Fusion
Wang Zou, Xia Sun, Maofu Liu, Yaqiong Xing, Xiaodi Zhao, Jun Feng   +5 more
openaire   +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

Enhanced Packed Marker with Entity Information for Aspect Sentiment Triplet Extraction

Annual International ACM SIGIR Conference on Research and Development in Information Retrieval
Aspect sentiment triplet extraction (ASTE) is an emerging sentiment analysis task that aims to extract sentiment triplets from review sentences. Each sentiment triplet consists of an aspect, corresponding opinion, and sentiment.
You Li, Xupeng Zeng, Yixiao Zeng, Yuming Lin   +3 more
semanticscholar   +1 more source