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End-to-end aspect category sentiment analysis based on type graph convolutional networks

SHAO Qing ZHANG Wenshuang WANG Shaojun

高技术通讯（英文版）2023，Vol.29Issue(3)：325-334,10.

高技术通讯（英文版）2023，Vol.29Issue(3)：325-334,10.DOI:10.3772/j.issn.1006-6748.2023.03.012

End-to-end aspect category sentiment analysis based on type graph convolutional networks

SHAO Qing ¹ZHANG Wenshuang ¹WANG Shaojun¹

作者信息

1. School of Optoelectronic Information and Intelligent Engineering,University of Shanghai for Science and Technology,Shanghai 200093,P.R.China
折叠

摘要

关键词

aspect-based sentiment analysis(ABSA)/bidirectional encoder representation from transformers(BERT)/type graph convolutional network(TGCN)/aspect category and senti-ment pair extraction

Key words

aspect-based sentiment analysis(ABSA)/bidirectional encoder representation from transformers(BERT)/type graph convolutional network(TGCN)/aspect category and senti-ment pair extraction

引用本文复制引用

SHAO Qing,ZHANG Wenshuang,WANG Shaojun..End-to-end aspect category sentiment analysis based on type graph convolutional networks[J].高技术通讯（英文版）,2023,29(3):325-334,10.

基金项目

Supported by the National Key Research and Development Program of China(No.2018YFB1702601). （No.2018YFB1702601）

高技术通讯（英文版）

OAEI

ISSN：1006-6748

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