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The recent proliferation of knowledge graphs (KGs) coupled with incomplete or partial information, in the form of missing relations (links) between entities, has fueled a lot of research on knowledge base completion (also known as relation prediction).
Statistical predicate invention
Stanley Kok and Pedro Domingos. 2007 · 2007
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Global learning of focused entailment graphs
Jonathan Berant, Ido Dagan, and Jacob Goldberger. 2010 · 2010
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A three-way model for collective learning on multi-relational data
Maximilian Nickel, Volker Tresp, and Hans-Peter Kriegel. 2011 · 2011
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Link prediction in complex networks based on cluster information
Jorge Carlos Valverde-Rebaza and Alneu de Andrade Lopes. 2012 · 2012
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Semantic parsing on freebase from question-answer pairs
Jonathan Berant, Andrew Chou, Roy Frostig, and Percy Liang. 2013 · 2013
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Translating embeddings for modeling multi-relational data
Antoine Bordes, Nicolas Usunier, Alberto Garcia-Duran, Jason Weston, and Oksana Yakhnenko. 2013 · 2013
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Reasoning with neural tensor networks for knowledge base completion
Richard Socher, Danqi Chen, Christopher D Manning, and Andrew Ng. 2013a · 2013
Earlier work this paper cites.
Reasoning with neural tensor networks for knowledge base completion
Richard Socher, Danqi Chen, Christopher D Manning, and Andrew Ng. 2013b · 2013
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Semantic parsing via paraphrasing
Jonathan Berant and Percy Liang. 2014 · 2014
Earlier work this paper cites.
Knowledge base completion via search-based question answering
Robert West, Evgeniy Gabrilovich, Kevin Murphy, Shaohua Sun, Rahul Gupta, and Dekang Lin. 2014 · 2014
Earlier work this paper cites.
Efficient global learning of entailment graphs
Jonathan Berant, Noga Alon, Ido Dagan, and Jacob Goldberger. 2015 · 2015
Cited alongside, same era.
Textual entailment graphs
LILI KOTLERMAN, IDO DAGAN, BERNARDO MAGNINI, and LUISA BENTIVOGLI. 2015 · 2015
Cited alongside, same era.
Modeling relation paths for representation learning of knowledge bases
Yankai Lin, Zhiyuan Liu, Huanbo Luan, Maosong Sun, Siwei Rao, and Song Liu. 2015 · 2015
Cited alongside, same era.
Representing text for joint embedding of text and knowledge bases
Kristina Toutanova, Danqi Chen, Patrick Pantel, Hoifung Poon, Pallavi Choudhury, and Michael Gamon. 2015 · 2015
Cited alongside, same era.
Embedding Entities and Relations for Learning and Inference in Knowledge Bases
Bishan Yang, Wen-tau Yih, Xiaodong He, Jianfeng Gao, and Li Deng. 2015 · 2015
Cited alongside, same era.
Holographic embeddings of knowledge graphs
Maximilian Nickel, Lorenzo Rosasco, Tomaso A Poggio, et al. 2016 · 2016
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Ł ukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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Deeppath: A reinforcement learning method for knowledge graph reasoning
Wenhan Xiong, Thien Hoang, and William Yang Wang. 2017 · 2017
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Convolutional 2d knowledge graph embeddings
Tim Dettmers, Pasquale Minervini, Pontus Stenetorp, and Sebastian Riedel. 2018 · 2018
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Wdaqua-core1: a question answering service for rdf knowledge bases
Dennis Diefenbach, Kamal Singh, and Pierre Maret. 2018 · 2018
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Multi-hop knowledge graph reasoning with reward shaping
Xi Victoria Lin, Richard Socher, and Caiming Xiong. 2018 · 2018
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A novel embedding model for knowledge base completion based on convolutional neural network
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Cited alongside, same era.
Question answering over knowledge base with neural attention combining global knowledge information
Yuanzhe Zhang, Kang Liu, Shizhu He, Guoliang Ji, Zhanyi Liu, Hua Wu, and Jun Zhao. 2016 · 2016
Cited alongside, same era.
Learning symmetric collaborative dialogue agents with dynamic knowledge graph embeddings
He He, Anusha Balakrishnan, Mihail Eric, and Percy Liang. 2017 · 2017
Cited alongside, same era.
Evaluating persuasion strategies and deep reinforcement learning methods for negotiation dialogue agents
Simon Keizer, Markus Guhe, Heriberto Cuayahuitl, Ioannis Efstathiou, Klaus-Peter Engelbrecht, Mihai Dobre, Alex Lascarides, and Oliver Lemon. 2017 · 2017
Cited alongside, same era.
Semi-supervised classification with graph convolutional networks
Thomas N. Kipf and Max Welling. 2017 · 2017
Cited alongside, same era.
Dai Quoc Nguyen, Tu Dinh Nguyen, Dat Quoc Nguyen, and Dinh Phung. 2018 · 2018
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Modeling relational data with graph convolutional networks
Michael Schlichtkrull, Thomas N Kipf, Peter Bloem, Rianne van den Berg, Ivan Titov, and Max Welling. 2018 · 2018
Later among the works it cites.
Graph Attention Networks
Petar Veličković, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Liò, and Yoshua Bengio. 2018 · 2018
Later among the works it cites.
Complex embeddings for simple link prediction
Théo Trouillon, Johannes Welbl, Sebastian Riedel, Éric Gaussier, and Guillaume Bouchard. 2016 · 2080
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