GeDa: Improving training data with large language models for Aspect Sentiment Triplet Extraction-Reference-Cited by-同舟云学术

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GeDa: Improving training data with large language models for Aspect Sentiment Triplet Extraction

Published:2024-10 Issue: Volume:301 Page:112289
ISSN:0950-7051
Container-title:Knowledge-Based Systems
language:en
Short-container-title:Knowledge-Based Systems

Author:

Mai Weixing^ORCID,Zhang Zhengxuan,Chen Yifan,Li Kuntao,Xue Yun^ORCID

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference38 articles.

1. Aspect based sentiment analysis using deep learning approaches: A survey;Chauhan;Comp. Sci. Rev.,2023

2. A review on sentiment analysis from social media platforms;Rodríguez-Ibánez;Expert Syst. Appl.,2023

3. Enhancing aspect term extraction with soft prototypes;Chen,2020

4. Latent opinions transfer network for target-oriented opinion words extraction;Wu,2020

5. Relational graph attention network for aspect-based sentiment analysis;Wang,2020

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