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Text summarization and sentiment classification both aim to capture the main ideas of the text but at different levels.
Automatic evaluation of summaries using n-gram co-occurrence statistics
Chin-Yew Lin and Eduard H. Hovy · 2003
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A joint model of text and aspect ratings for sentiment summarization
Ivan Titov and Ryan T. McDonald · 2008
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Sentiment summarization: Evaluating and learning user preferences
Kevin Lerman, Sasha Blair-Goldensohn, and Ryan T. McDonald · 2009
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Real time tweet summarization and sentiment analysis of game tournament
Vikrant Hole and Mukta Takalikar · 2013
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On the difficulty of training recurrent neural networks
Razvan Pascanu, Tomas Mikolov, and Yoshua Bengio · 2013
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Convolutional neural networks for sentence classification
Yoon Kim · 2014
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2014
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Sequence to sequence learning with neural networks
Ilya Sutskever, Oriol Vinyals, and Quoc V. Le · 2014
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LCSTS: A large scale chinese short text summarization dataset
Baotian Hu, Qingcai Chen, and Fangze Zhu · 2015
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Summarization and sentiment analysis from user health posts
Vinod L Mane, Suja S Panicker, and Vidya B Patil · 2015
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A neural attention model for abstractive sentence summarization
Alexander M. Rush, Sumit Chopra, and Jason Weston · 2015
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Document modeling with gated recurrent neural network for sentiment classification
Duyu Tang, Bing Qin, and Ting Liu · 2015
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Distraction-based neural networks for modeling documents
Qian Chen, Xiaodan Zhu, Zhenhua Ling, Si Wei, and Hui Jiang · 2016
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Neural summarization by extracting sentences and words
Jianpeng Cheng and Mirella Lapata · 2016
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Abstractive sentence summarization with attentive recurrent neural networks
Sumit Chopra, Michael Auli, and Alexander M. Rush · 2016
Neural headline generation on abstract meaning representation
Sho Takase, Jun Suzuki, Naoaki Okazaki, Tsutomu Hirao, and Masaaki Nagata · 2016
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Improving multi-document summarization via text classification
Ziqiang Cao, Wenjie Li, Sujian Li, and Furu Wei · 2017
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Improving semantic relevance for sequence-to-sequence learning of chinese social media text summarization
Shuming Ma, Xu Sun, Jingjing Xu, Houfeng Wang, Wenjie Li, and Qi Su · 2017
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Get to the point: Summarization with pointer-generator networks
Abigail See, Peter J. Liu, and Christopher D. Manning · 2017
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meprop: Sparsified back propagation for accelerated deep learning with reduced overfitting
Xu Sun, Xuancheng Ren, Shuming Ma, and Houfeng Wang · 2017
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Label embedding network: Learning label representation for soft training of deep networks
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Incorporating copying mechanism in sequence-to-sequence learning
Jiatao Gu, Zhengdong Lu, Hang Li, and Victor O. K. Li · 2016
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Ups and downs: Modeling the visual evolution of fashion trends with one-class collaborative filtering
Ruining He and Julian McAuley · 2016
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Abstractive text summarization using sequence-to-sequence rnns and beyond
Ramesh Nallapati, Bowen Zhou, Cícero Nogueira dos Santos, Çaglar Gülçehre, and Bing Xiang · 2016
Cited alongside, same era.
Xu Sun, Bingzhen Wei, Xuancheng Ren, and Shuming Ma · 2017
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Query and output: Generating words by querying distributed word representations for paraphrase generation
Shuming Ma, Xu Sun, Wei Li, Sujian Li, Wenjie Li, and Xuancheng Ren · 2018
Closest in time.
Jingjing Xu, Xu Sun, Xuancheng Ren, Junyang Lin, Binzhen Wei, and Wei Li · 2018
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Unpaired sentiment-to-sentiment translation: A cycled reinforcement learning approach
Jingjing Xu, Xu Sun, Qi Zeng, Xiaodong Zhang, Xuancheng Ren, Houfeng Wang, and Wenjie Li · 2018
Closest in time.