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Script event prediction requires a model to predict the subsequent event given an existing event context.
Scripts, plans, goals, and understanding: An inquiry into human knowledge structures (artificial intelligence series)
Roger C Schank and Robert P Abelson · 1977
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A new model for learning in graph domains
Marco Gori, Gabriele Monfardini, and Franco Scarselli · 2005
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Linguistically motivated large-scale nlp with c&c and boxer
James R Curran, Stephen Clark, and Johan Bos · 2007
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Learning plan networks in conversational video games
Jeffrey David Orkin · 2007
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Unsupervised learning of narrative event chains
Nathanael Chambers and Daniel Jurafsky · 2008
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Skip n-grams and ranking functions for predicting script events
Bram Jans, Steven Bethard, Ivan Vulić, and Marie Francine Moens · 2012
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Story generation with crowdsourced plot graphs
Boyang Li, Stephen Lee-Urban, George Johnston, and Mark O. Riedl · 2013
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Distributed representations of words and phrases and their compositionality
Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean · 2013
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Learning phrase representations using rnn encoder–decoder for statistical machine translation
Kyunghyun Cho, Bart van Merrienboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio · 2014
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Deepwalk: online learning of social representations
Bryan Perozzi, Rami Alrfou, and Steven Skiena · 2014
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Statistical script learning with multi-argument events
Karl Pichotta and Raymond J Mooney · 2014
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Neural machine translation by jointly learning to align and translate
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio · 2015
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Convolutional networks on graphs for learning molecular fingerprints
David K Duvenaud, Dougal Maclaurin, Jorge Iparraguirre, Rafael Bombarell, Timothy Hirzel, Alán Aspuru-Guzik, and Ryan P Adams · 2015
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Construction and evaluation of event graphs
Line: Large-scale information network embedding
Jian Tang, Meng Qu, Mingzhe Wang, Ming Zhang, Jun Yan, and Qiaozhu Mei · 2015
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What happens next? event prediction using a compositional neural network model
Mark Granroth-Wilding and Stephen Clark · 2016
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node2vec: Scalable feature learning for networks
A Grover and J Leskovec · 2016
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Gated graph sequence neural networks
Yujia Li, Daniel Tarlow, Marc Brockschmidt, and Richard Zemel · 2016
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Using sentence-level lstm language models for script inference
Karl Pichotta and Raymond J Mooney · 2016
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Semi-supervised classification with graph convolutional networks
Thomas N Kipf and Max Welling · 2017
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Goran Glavaš and Jan Šnajder · 2015
Cited alongside, same era.
From word embeddings to document distances
Matt Kusner, Yu Sun, Nicholas Kolkin, and Kilian Weinberger · 2015
Cited alongside, same era.
Learning statistical scripts with lstm recurrent neural networks
Karl Pichotta and Raymond J Mooney · 2015
Cited alongside, same era.
Integrating order information and event relation for script event prediction
Zhongqing Wang, Yue Zhang, and Ching-Yun Chang · 2017
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Constructing and embedding abstract event causality networks from text snippets
Sendong Zhao, Quan Wang, Sean Massung, Bing Qin, Ting Liu, Bin Wang, and ChengXiang Zhai · 2017
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