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Dual Graph Convolutional Networks for Aspect-based ...

Proceedings of the 59th Annual Meeting of the Association for Computational Linguisticsand the 11th International Joint Conference on Natural Language Processing, pages 6319 6329 August 1 6, 2021. 2021 Association for Computational Linguistics6319 Dual Graph Convolutional Networks for Aspect-based Sentiment AnalysisRuifan Li1 , Hao Chen1, Fangxiang Feng1,Zhanyu Ma1, Xiaojie WANG1, and Eduard Hovy21 School of Artificial Intelligence, Beijing University of Posts and Telecommunications, China2 Language Technologies Institute, Carnegie Mellon University, USA{rfli, ccchenhao997, fxfeng, mazhanyu, sentiment analysis is a fine-grained sentiment classification , Graph neural Networks over depen-dency trees have been explored to explicitlymodel connections between aspects and opin-ion words. However, the improvement is lim-ited due to the inaccuracy of the dependencyparsing results and the informal expressionsand complexity of online reviews.}

in linguistics and designed hierarchical syntactic and lexical graphs. (Liang et al.,2020) constructed aspect-focused and inter-aspect graphs to learn de-pendency feature of the key aspect words and sen-timent relations between different aspects. In this paper, we propose a GCN based method combining syntactic and semantic features. We use

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