RDGCN: Reinforced Dependency Graph Convolutional Network for Aspect-based Sentiment Analysis
Author:
Affiliation:
1. Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China
2. Beihang University, Beijing, China
3. University of Science and Technology of China, Hefei, China
4. University of Illinois Chicago, Chicago, USA
Funder
NSFC
National Key R&D Program of China
NSF (National Science Foundation)
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3616855.3635775
Reference43 articles.
1. Chenhua Chen Zhiyang Teng and Yue Zhang. 2020. Inducing target-specific latent structures for aspect sentiment classification. In EMNLP. 5596--5607.
2. Hao Chen Zepeng Zhai Fangxiang Feng Ruifan Li and Xiaojie Wang. 2022. Enhanced multi-channel graph convolutional network for aspect sentiment triplet extraction. In ACL. 2974--2985.
3. Peng Chen Zhongqian Sun Lidong Bing and Wei Yang. 2017. Recurrent attention network on memory for aspect sentiment analysis. In EMNLP. 452--461.
4. Junqi Dai Hang Yan Tianxiang Sun Pengfei Liu and Xipeng Qiu. 2021. Does syntax matter? A strong baseline for aspect-based sentiment analysis with RoBERTa. In NAACL. 1816--1829.
5. Deep Learning for Aspect-Based Sentiment Analysis: A Comparative Review
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