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Syntax-Aware Graph Attention Network for Aspect-Level Sentiment Classification
2020
Proceedings of the 28th International Conference on Computational Linguistics
unpublished
Preserved Fulltext
Aspect-level sentiment classification aims to distinguish the sentiment polarities over aspect terms in a sentence. ...
In this paper, we exploit syntactic awareness to the model by the graph attention network on the dependency tree structure and external pre-training knowledge by BERT language model, which helps to model ...
Conclusion In this paper, we proposed a model named SAGAT for aspect-level sentiment classification. ...
doi:10.18653/v1/2020.coling-main.69
fatcat:puzlhupfwnauzmhtew72syu6lq
Syntax-Aware Aspect Level Sentiment Classification with Graph Attention Networks
[article]
2019
arXiv
pre-print
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In this paper, we propose a novel target-dependent graph attention network (TD-GAT) for aspect level sentiment classification, which explicitly utilizes the dependency relationship among words. ...
Aspect level sentiment classification aims to identify the sentiment expressed towards an aspect given a context sentence. ...
Conclusion In this paper, we propose a novel target-dependent graph attention neural network for aspect level sentiment classification. ...
arXiv:1909.02606v1
fatcat:kpifsqpvazdjhpfhjmfyrbr2rq
Syntax-Aware Aspect Level Sentiment Classification with Graph Attention Networks
2019
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
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In this paper, we propose a novel target-dependent graph attention network (TD-GAT) for aspect level sentiment classification, which explicitly utilizes the dependency relationship among words. ...
Aspect level sentiment classication aims to identify the sentiment expressed towards an aspect given a context sentence. ...
Conclusion In this paper, we propose a novel target-dependent graph attention neural network for aspect level sentiment classification. ...
doi:10.18653/v1/d19-1549
dblp:conf/emnlp/HuangC19a
fatcat:debdzy7vlfhjxbg3xlzybiqpga
Understand me, if you refer to Aspect Knowledge: Knowledge-aware Gated Recurrent Memory Network
[article]
2022
arXiv
pre-print
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2022 pre-print arXiv:2108.02352v2 fatcat:tk4kdtlotbatjpkm5til3zhj4qOther Versions
Aspect-level sentiment classification (ASC) aims to predict the fine-grained sentiment polarity towards a given aspect mentioned in a review. ...
Our model includes three key components: (1) a knowledge-aware gated recurrent memory network recurrently integrates dynamically summarized aspect knowledge; (2) a dual syntax graph network combines both ...
and use h cls for sentiment classification. • AEN-BERT [46] adopts BERT encoder and uses the attentional encoder network to model the interactions between the aspect and context. 5) Both of syntax graph ...
arXiv:2108.02352v3
fatcat:jg45oufaqbgxtcxoakg3d5wiam
Exploiting Typed Syntactic Dependencies for Targeted Sentiment Classification Using Graph Attention Neural Network
[article]
2020
arXiv
pre-print
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2020 pre-print arXiv:2002.09685v1 fatcat:2fbkjpdcsfg5tjube6uuouw4kmOther Versions
Recently, graph neural network has been investigated for integrating dependency syntax for the task, achieving the state-of-the-art results. ...
To solve the problem, we investigate a novel relational graph attention network that integrates typed syntactic dependency information. ...
The above results indicates that syntax is helpful for targeted sentiment classification. ...
arXiv:2002.09685v2
fatcat:3mkjvrnfkfcztfzfntmpsnhatm
DigNet: Digging Clues from Local-Global Interactive Graph for Aspect-level Sentiment Classification
[article]
2022
arXiv
pre-print
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In aspect-level sentiment classification (ASC), state-of-the-art models encode either syntax graph or relation graph to capture the local syntactic information or global relational information. ...
In this way, the local syntactic and global relational information can be reconciled as a whole in understanding the aspect-level sentiment. ...
Tsang was also supported by A * STAR Centre for Frontier AI Research (CFAR). ...
arXiv:2201.00989v2
fatcat:fg3ru5t4ibgrtb5rhyvh3ymm5i
Aspect-based Sentiment Classification with Aspect-specific Graph Convolutional Networks
[article]
2019
arXiv
pre-print
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Due to their inherent capability in semantic alignment of aspects and their context words, attention mechanism and Convolutional Neural Networks (CNNs) are widely applied for aspect-based sentiment classification ...
clues for judging aspect sentiment. ...
Introduction Aspect-based (also known as aspect-level) sentiment classification aims at identifying the sentiment polarities of aspects explicitly given in sentences. ...
arXiv:1909.03477v2
fatcat:l2aaph7objchnk6jljnesr6vna
Aspect-based Sentiment Classification with Aspect-specific Graph Convolutional Networks
2019
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
Preserved Fulltext
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Due to their inherent capability in semantic alignment of aspects and their context words, attention mechanism and Convolutional Neural Networks (CNNs) are widely applied for aspect-based sentiment classification ...
clues for judging aspect sentiment. ...
Introduction Aspect-based (also known as aspect-level) sentiment classification aims at identifying the sentiment polarities of aspects explicitly given in sentences. ...
doi:10.18653/v1/d19-1464
dblp:conf/emnlp/ZhangLS19
fatcat:m3ygym3qi5atberu6gztms7zsi
Selective Attention Based Graph Convolutional Networks for Aspect-Level Sentiment Classification
[article]
2021
arXiv
pre-print
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2020 pre-print arXiv:1910.10857v3 fatcat:l6ubp7plhrbkrkfaqf4wqb6e3yOther Versions
Aspect-level sentiment classification aims to identify the sentiment polarity towards a specific aspect term in a sentence. ...
In this paper, we propose to employ graph convolutional networks (GCNs) on the dependency tree to learn syntax-aware representations of aspect terms. ...
Conclusions We propose a selective attention based GCN model for the aspect-level sentiment classification task. ...
arXiv:1910.10857v4
fatcat:5w2nqjodfzdrxjojndqkzzno74
Relational Graph Attention Network for Aspect-based Sentiment Analysis
[article]
2020
arXiv
pre-print
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Then, we propose a relational graph attention network (R-GAT) to encode the new tree structure for sentiment prediction. ...
our approach, and the performance of the graph attention network (GAT) is significantly improved as a consequence. ...
Acknowledgments The work was supported by the Fundamental Research Funds for the Central Universities (No.19lgpy220) and the Program for Guangdong Introducing Innovative and Entrepreneurial Teams (No.2017ZT07X355 ...
arXiv:2004.12362v1
fatcat:kvinzmao6vakrglj5qhf7rbfum
Learn from Structural Scope: Improving Aspect-Level Sentiment Analysis with Hybrid Graph Convolutional Networks
[article]
2022
arXiv
pre-print
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Aspect-level sentiment analysis aims to determine the sentiment polarity towards a specific target in a sentence. ...
To jointly learn structural Scope and predict the sentiment polarity, we propose a hybrid graph convolutional network (HGCN) to synthesize information from constituency tree and dependency tree, exploring ...
Introduction Aspect-level sentiment analysis (ALSA) is a fine-grained classification task, aiming at identifying opinion polarities towards specific entities called targets. ...
arXiv:2204.12784v1
fatcat:aehhhzp7dnbc7kmrodvlp6etdu
Syntactic Edge-Enhanced Graph Convolutional Networks for Aspect-Level Sentiment Classification with Interactive Attention
2020
IEEE Access
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In this article, we propose a syntactic edge-enhanced graph convolutional network (ASEGCN) for aspect-level sentiment classification with interactive attention. ...
Aspect-level sentiment classification is a hot research topic in natural language processing (NLP). ...
ACKNOWLEDGMENT This work was supported in part by the Fundamental Research Funds for the Central Universities (No. KJ02072019-0383). We thank the anonymous reviewers for their insightful comments. ...
doi:10.1109/access.2020.3019277
fatcat:o6dl66f37nb33gtwi2q7dmwbtm
Graph Convolutional Networks with Bidirectional Attention for Aspect-Based Sentiment Classification
2021
Applied Sciences
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Aspect-based sentiment classification aims at determining the corresponding sentiment of a particular aspect. ...
In this paper, we propose an effective and novel method using attention mechanism and graph convolutional network (ATGCN). ...
Acknowledgments: Thanks to all commenters for their valuable comments.
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/app11041528
fatcat:khq4a74zgrdfdnuhvkyu7pom2u
Knowledge Graph Augmented Network Towards Multiview Representation Learning for Aspect-based Sentiment Analysis
[article]
2022
arXiv
pre-print
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Aspect-based sentiment analysis (ABSA) is a fine-grained task of sentiment analysis. ...
Then, KGAN integrates the knowledge graphs into the embedding space, based on which the aspect-specific knowledge representations are further obtained via an attention mechanism. ...
aspect-level sentiment classification. • RAM [51] : This method employs multiple attention and memory networks to capture the aspect-specific sentence representation. • TNet-AS [6] : Using the CNN as ...
arXiv:2201.04831v1
fatcat:3ksibbglbzablmucuw22rjrlom
Learning Implicit Sentiment in Aspect-based Sentiment Analysis with Supervised Contrastive Pre-Training
[article]
2021
arXiv
pre-print
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However, recent neural network-based approaches paid little attention to implicit sentiment entailed in the reviews. ...
Aspect-based sentiment analysis aims to identify the sentiment polarity of a specific aspect in product reviews. ...
Acknowledgments The authors wish to thank the anonymous reviewers for their helpful comments. ...
arXiv:2111.02194v1
fatcat:y5rtwl4j4rg2xctlm7c5xclifa
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