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Knowledge graphs contain knowledge about the world and provide a structured representation of this knowledge.
The expression of a tensor or a polyadic as a sum of products
Frank L Hitchcock · 1927
Earlier work this paper cites.
Approximations by superpositions of a sigmoidal function
George Cybenko · 1989
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Approximation capabilities of multilayer feedforward networks
Kurt Hornik · 1991
Earlier work this paper cites.
Wordnet: a lexical database for english
George A Miller · 1995
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Introduction to statistical relational learning
Lise Getoor and Ben Taskar · 2007
Earlier work this paper cites.
Freebase: a collaboratively created graph database for structuring human knowledge
Kurt Bollacker, Colin Evans, Praveen Paritosh, Tim Sturge, and Jamie Taylor · 2008
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Relational retrieval using a combination of path-constrained random walks
Ni Lao and William W Cohen · 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
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Factorizing yago: scalable machine learning for linked data
Maximilian Nickel, Volker Tresp, and Hans-Peter Kriegel · 2012
Earlier work this paper cites.
Irreflexive and hierarchical relations as translations
Antoine Bordes, Nicolas Usunier, Alberto Garcia-Duran, Jason Weston, and Oksana Yakhnenko · 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
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Reasoning with neural tensor networks for knowledge base completion
Richard Socher, Danqi Chen, Christopher D Manning, and Andrew Ng · 2013
Earlier work this paper cites.
Knowledge vault: A web-scale approach to probabilistic knowledge fusion
Xin Dong, Evgeniy Gabrilovich, Geremy Heitz, Wilko Horn, Ni Lao, Kevin Murphy, Thomas Strohmann, Shaohua Sun, and Wei Zhang · 2014
Earlier work this paper cites.
Reducing the rank in relational factorization models by including observable patterns
Maximilian Nickel, Xueyan Jiang, and Volker Tresp · 2014
Earlier work this paper cites.
Low-dimensional embeddings of logic
Tim Rocktäschel, Matko Bošnjak, Sameer Singh, and Sebastian Riedel · 2014
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Knowledge graph embedding by translating on hyperplanes
Zhen Wang, Jianwen Zhang, Jianlin Feng, and Zheng Chen · 2014
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Knowledge graph embedding via dynamic mapping matrix
Guoliang Ji, Shizhu He, Liheng Xu, Kang Liu, and Jun Zhao · 2015
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Modeling relation paths for representation learning of knowledge bases
Yankai Lin, Zhiyuan Liu, Huanbo Luan, Maosong Sun, Siwei Rao, and Song Liu · 2015
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Learning entity and relation embeddings for knowledge graph completion
Yankai Lin, Zhiyuan Liu, Maosong Sun, Yang Liu, and Xuan Zhu · 2015
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Knowledge base completion using embeddings and rules
Quan Wang, Bin Wang, Li Guo, et al · 2015
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Large-scale knowledge base completion: Inferring via grounding network sampling over selected instances
Zhuoyu Wei, Jun Zhao, Kang Liu, Zhenyu Qi, Zhengya Sun, and Guanhua Tian · 2015
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Embedding entities and relations for learning and inference in knowledge bases
Knowledge base completion: Baselines strike back
Rudolf Kadlec, Ondrej Bajgar, and Jan Kleindienst · 2017
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Regularizing knowledge graph embeddings via equivalence and inversion axioms
Pasquale Minervini, Luca Costabello, Emir Muñoz, Vít Nováček, and Pierre-Yves Vandenbussche · 2017
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An overview of embedding models of entities and relationships for knowledge base completion
Dat Quoc Nguyen · 2017
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End-to-end differentiable proving
Tim Rocktäschel and Sebastian Riedel · 2017
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A simple neural network module for relational reasoning
Adam Santoro, David Raposo, David G Barrett, Mateusz Malinowski, Razvan Pascanu, Peter Battaglia, and Tim Lillicrap · 2017
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Bishan Yang, Wen-tau Yih, Xiaodong He, Jianfeng Gao, and Li Deng · 2015
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Tensorflow: Large-scale machine learning on heterogeneous distributed systems
Martın Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, et al · 2016
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Statistical relational artificial intelligence: Logic, probability, and computation
Luc De Raedt, Kristian Kersting, Sriraam Natarajan, and David Poole · 2016
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Knowledge graph embedding by flexible translation
Jun Feng, Minlie Huang, Mingdong Wang, Mantong Zhou, Yu Hao, and Xiaoyan Zhu · 2016
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Jointly embedding knowledge graphs and logical rules
Shu Guo, Quan Wang, Lihong Wang, Bin Wang, and Li Guo · 2016
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Stranse: a novel embedding model of entities and relationships in knowledge bases
Dat Quoc Nguyen, Kairit Sirts, Lizhen Qu, and Mark Johnson · 2016
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A review of relational machine learning for knowledge graphs
Maximilian Nickel, Kevin Murphy, Volker Tresp, and Evgeniy Gabrilovich · 2016
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Théo Trouillon and Maximilian Nickel · 2017
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Knowledge graph completion via complex tensor factorization
Théo Trouillon, Christopher R Dance, Johannes Welbl, Sebastian Riedel, Éric Gaussier, and Guillaume Bouchard · 2017
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Knowledge graph embedding: A survey of approaches and applications
Quan Wang, Zhendong Mao, Bin Wang, and Li Guo · 2017
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Visual translation embedding network for visual relation detection
Hanwang Zhang, Zawlin Kyaw, Shih-Fu Chang, and Tat-Seng Chua · 2017
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Convolutional 2d knowledge graph embeddings
Tim Dettmers, Pasquale Minervini, Pontus Stenetorp, and Sebastian Riedel · 2018
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Improving knowledge graph embedding using simple constraints
Boyang Ding, Quan Wang, Bin Wang, and Li Guo · 2018
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Relnn: A deep neural model for relational learning
Seyed Mehran Kazemi and David Poole · 2018
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Analogical inference for multi-relational embeddings
Hanxiao Liu, Yuexin Wu, and Yiming Yang · 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
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On multi-relational link prediction with bilinear models
Yanjie Wang, Rainer Gemulla, and Hui Li · 2018
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