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Aspect-based sentiment analysis (ABSA) is an NLP task that entails processing user-generated reviews to determine (i) the target being evaluated, (ii) the aspect category to which it belongs, and (iii) the sentiment expressed towards the target and aspect pair.
Utilizing bert for aspect-based sentiment analysis via constructing auxiliary sentence
Chi Sun, Luyao Huang, and Xipeng Qiu. 2019 · 1903
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Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Veselin Stoyanov, and Luke Zettlemoyer. 2019 · 1910
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Extracting opinion targets in a single and cross-domain setting with conditional random fields
Niklas Jakob and Iryna Gurevych. 2010 · 2010
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Syntactic patterns versus word alignment: Extracting opinion targets from online reviews
Kang Liu, Liheng Xu, and Jun Zhao. 2013 · 2013
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Open domain targeted sentiment
Margaret Mitchell, Jacqui Aguilar, Theresa Wilson, and Benjamin Van Durme. 2013 · 2013
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NRC-canada-2014: Detecting aspects and sentiment in customer reviews
Svetlana Kiritchenko, Xiaodan Zhu, Colin Cherry, and Saif Mohammad. 2014 · 2014
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A vector space approach for aspect-based sentiment analysis
Abdulaziz Alghunaim. 2015 · 2015
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A neural attention model for abstractive sentence summarization
Alexander M. Rush, Sumit Chopra, and Jason Weston. 2015 · 2015
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Neural networks for open domain targeted sentiment
Meishan Zhang, Yue Zhang, and Duy-Tin Vo. 2015 · 2015
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Attention-based LSTM for aspect-level sentiment classification
Yequan Wang, Minlie Huang, Xiaoyan Zhu, and Li Zhao. 2016 · 2016
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Unsupervised word and dependency path embeddings for aspect term extraction
Yichun Yin, Furu Wei, Li Dong, Kaimeng Xu, Ming Zhang, and Ming Zhou. 2016 · 2016
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Deep multi-task learning for aspect term extraction with memory interaction
Xin Li and Wai Lam. 2017 · 2017
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Coupled multi-layer attentions for co-extraction of aspect and opinion terms
Wenya Wang, Sinno Jialin Pan, Daniel Dahlmeier, and Xiaokui Xiao. 2017 · 2017
Cited alongside, same era.
MTNA: A neural multi-task model for aspect category classification and aspect term extraction on restaurant reviews
Wei Xue, Wubai Zhou, Tao Li, and Qing Wang. 2017 · 2017
Cited alongside, same era.
Aspect based sentiment analysis into the wild
Caroline Brun and Vassilina Nikoulina. 2018 · 2018
Cited alongside, same era.
Recurrent entity networks with delayed memory update for targeted aspect-based sentiment analysis
Fei Liu, Trevor Cohn, and Timothy Baldwin. 2018 · 2018
Cited alongside, same era.
Improving aspect term extraction with bidirectional dependency tree representation
Huaishao Luo, Tianrui Li, Bing Liu, Bin Wang, and Herwig Unger. 2018 · 2018
Cited alongside, same era.
Context-aware embedding for targeted aspect-based sentiment analysis
Bin Liang, Jiachen Du, Ruifeng Xu, Binyang Li, and Hejiao Huang. 2019 · 2019
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Roberta: A robustly optimized bert pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 2019
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DOER: Dual cross-shared RNN for aspect term-polarity co-extraction
Huaishao Luo, Tianrui Li, Bing Liu, and Junbo Zhang. 2019 · 2019
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Aspect category detection via topic-attention network
Sajad Movahedi, Erfan Ghadery, Heshaam Faili, and Azadeh Shakery. 2019 · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeff Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2019 · 2019
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Bert post-training for review reading comprehension and aspect-based sentiment analysis
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Targeted aspect-based sentiment analysis via embedding commonsense knowledge into an attentive lstm
Yukun Ma, Haiyun Peng, and Erik Cambria. 2018 · 2018
Cited alongside, same era.
Joint aspect and polarity classification for aspect-based sentiment analysis with end-to-end neural networks
Martin Schmitt, Simon Steinheber, Konrad Schreiber, and Benjamin Roth. 2018 · 2018
Cited alongside, same era.
Double embeddings and CNN-based sequence labeling for aspect extraction
Hu Xu, Bing Liu, Lei Shu, and Philip S. Yu. 2018 · 2018
Cited alongside, same era.
Aspect based sentiment analysis with gated convolutional networks
Wei Xue and Tao Li. 2018 · 2018
Cited alongside, same era.
Bert: Pre-training of deep bidirectional transformers for language understanding
J. Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Cited alongside, same era.
CAN: Constrained attention networks for multi-aspect sentiment analysis
Mengting Hu, Shiwan Zhao, Li Zhang, Keke Cai, Zhong Su, Renhong Cheng, and Xiaowei Shen. 2019a · 2019
Cited alongside, same era.
A unified model for opinion target extraction and target sentiment prediction
Xin Li, Lidong Bing, Piji Li, and Wai Lam. 2019 · 2019
Cited alongside, same era.
Hu Xu, Bing Liu, Lei Shu, and Philip S. Yu. 2019 · 2019
Later among the works it cites.
Enhancing attention-based lstm with position context for aspect-level sentiment classification
Jiangfeng Zeng, Xiao Ma, and Ke Zhou. 2019 · 2019
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Enhancing bert representation with context-aware embedding for aspect-based sentiment analysis
Xinlong Li, Xingyu Fu, Guangluan Xu, Yang Yang, Jiuniu Wang, Li Jin, Qing Liu, and Tianyuan Xiang. 2020 · 2020
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2020 · 2020
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Attention mechanism with gated recurrent unit using convolutional neural network for aspect level opinion mining
Meesala Shobha Rani and Sumathy Subramanian. 2020 · 2020
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Target-aspect-sentiment joint detection for aspect-based sentiment analysis
Hai Wan, Y. Yang, Jianfeng Du, Y. Liu, Kunxun Qi, and J. Pan. 2020 · 2020
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Context-guided bert for targeted aspect-based sentiment analysis
Zhengxuan Wu and Desmond C. Ong. 2020 · 2020
Later among the works it cites.