Convolutional Neural Networks for Sentence Classification

Keywords

Convolutional neural network, Computer science, Sentence, Artificial intelligence, Natural language processing

References

• ADADELTA: An Adaptive Learning Rate MethodMatthew D. Zeiler — 2012
• Fast dropout trainingSida Wang, Christopher D. Manning — 2013
• Semi-Supervised Recursive Autoencoders for Predicting Sentiment DistributionsRichard Socher, Jeffrey Pennington, Eric Huang — 2011
• Learning Discriminative Projections for Text Similarity MeasuresWen-tau Yih, Kristina Toutanova, John Platt — 2011
• Semantic Compositionality through Recursive Matrix-Vector SpacesRichard Socher, Brody Huval, Christopher D. Manning — 2012
• Improving neural networks by preventing co-adaptation of feature detectorsGeoffrey E. Hinton, Nitish Srivastava, Alex Krizhevsky — 2012
• Annotating Expressions of Opinions and Emotions in LanguageJanyce Wiebe, Theresa Wilson, Claire Cardie — 2005
• From symbolic to sub-symbolic information in question classificationJoão Silva, Luísa Coheur, Ana Cristina Mendes — 2011
• CNN Features Off-the-Shelf: An Astounding Baseline for RecognitionAli Sharif Razavian, Hossein Azizpour, Josephine Sullivan — 2014
• Learning Question ClassifiersXin Li, Dan Roth — 2002
• Gradient-based learning applied to document recognitionYann LeCun, Léon Bottou, Yoshua Bengio — 1998
• A Sentimental Education: Sentiment Analysis Using Subjectivity Summarization Based on Minimum CutsBo Pang, Lillian Lee — 2004
• A Statistical Parsing Framework for Sentiment ClassificationLi Dong, Furu Wei, Shujie Liu — 2014
• A Convolutional Neural Network for Modelling SentencesNal Kalchbrenner, Edward Grefenstette, Phil Blunsom — 2014
• The Role of Syntax in Vector Space Models of Compositional SemanticsKarl Moritz Hermann, Phil Blunsom — 2013
• Distributed Representations of Sentences and DocumentsQuoc V. Le, Tomáš Mikolov — 2014
• Dependency Tree-based Sentiment Classification using CRFs with Hidden VariablesTetsuji Nakagawa, Kentaro Inui, Sadao Kurohashi — 2010
• A neural probabilistic language modelY. Bengio, Réjean Ducharme, P. Vincent — 2003
• Speech recognition with deep recurrent neural networksAlex Graves, Abdelrahman Mohamed, Geoffrey E. Hinton — 2013
• Distributed Representations of Words and Phrases and their CompositionalityTomáš Mikolov, Ilya Sutskever, Kai Chen — 2013

Cited by

• Automatic Determination of the Need for Intravenous Contrast in Musculoskeletal MRI Examinations Using IBM Watson’s Natural Language Processing Algorithm杨青 — 2018
• Protein-Protein Interaction Article Classification Using a Convolutional Recurrent Neural Network with Pre-trained Word EmbeddingsG.A. Petzet — 2017
• Tumor gene expression data classification via sample expansion-based deep learningTeresa Cruz Sánchez — 2017
• Semisupervised Text Classification by Variational Autoencoder廣次 堀野 — 2020
• Generative-Discriminative Complementary LearningJerker Sundström — 2019
• A Novel Visual Representation on Text Using Diverse Conditional GAN for Visual RecognitionAbdul Hafeez‐Baig, Raj Gururajan, Heng Sheng Tsai — 2021
• Distilling Word Embeddings: An Encoding ApproachLili Mou, Ran Jia, Yan Xu — 2015
• Modelling input texts: from Tree Kernels to Deep LearningAliaksei Severyn — 2015
• How to Generate a Good Word EmbeddingSiwei Lai, Kang Liu, Shizhu He — 2015
• Local Translation Prediction with Global Sentence RepresentationJiajun Zhang — 2015
• Integrating word embeddings and traditional NLP features to measure textual entailment and semantic relatedness of sentence pairsJiang Zhao, Man Lan, Zheng-Yu Niu — 2015
• Tree-based Convolution: A New Neural Architecture for Sentence ModelingLili Mou, Hao Peng, Ge Li — 2015
• Learning multi-faceted representations of individuals from heterogeneous evidence using neural networksJiwei Li, Alan Ritter, Dan Jurafsky — 2015
• Text Understanding from ScratchXiang Zhang, Yann LeCun — 2015
• Semi-supervised Convolutional Neural Networks for Text Categorization via Region EmbeddingRie Johnson, Tong Zhang — 2015
• Erratum: “From Paraphrase Database to Compositional Paraphrase Model and Back”John Wieting, Mohit Bansal, Kevin Gimpel — 2015
• Effective Use of Word Order for Text Categorization with Convolutional Neural NetworksRie Johnson, Tong Zhang — 2014
• State of the art in statistical methods for language and speech processingJerome R. Bellegarda, Christof Monz — 2016
• Supervised Fine Tuning for Word Embedding with Integrated KnowledgeXuefeng Yang, Kezhi Mao — 2015
• Molding CNNs for text: non-linear, non-consecutive convolutionsTao Leí, Regina Barzilay, Tommi Jaakkola — 2015

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