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Embedding knowledge graphs (KGs) into continuous vector spaces is a focus of current research.
Learning effective and interpretable semantic models using non-negative sparse embedding
Brian Murphy, Partha Talukdar, and Tom Mitchell. 2012 · 1950
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Holographic embeddings of knowledge graphs
Maximilian Nickel, Lorenzo Rosasco, and Tomaso Poggio. 2016b · 1961
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Learning the parts of objects by non-negative matrix factorization
Daniel D. Lee and H. Sebastian Seung. 1999 · 1999
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Freebase: A collaboratively created graph database for structuring human knowledge
Kurt Bollacker, Colin Evans, Praveen Paritosh, Tim Sturge, and Jamie Taylor. 2008 · 2008
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Learning structured embeddings of knowledge bases
Antoine Bordes, Jason Weston, Ronan Collobert, and Yoshua Bengio. 2011 · 2011
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Adaptive subgradient methods for online learning and stochastic optimization
John Duchi, Elad Hazan, and Yoram Singer. 2011 · 2011
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Knowledge-based weak supervision for information extraction of overlapping relations
Raphael Hoffmann, Congle Zhang, Xiao Ling, Luke Zettlemoyer, and Daniel S. Weld. 2011 · 2011
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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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A latent factor model for highly multi-relational data
Rodolphe Jenatton, Nicolas L. Roux, Antoine Bordes, and Guillaume R. Obozinski. 2012 · 2012
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Translating embeddings for modeling multi-relational data
Antoine Bordes, Nicolas Usunier, Alberto García-Durán, 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 Y. Ng. 2013 · 2013
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A semantic matching energy function for learning with multi-relational data
Antoine Bordes, Xavier Glorot, Jason Weston, and Yoshua Bengio. 2014 · 2014
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Typed tensor decomposition of knowledge bases for relation extraction
Kai-Wei Chang, Wen-tau Yih, Bishan Yang, and Christopher Meek. 2014 · 2014
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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 · 2014
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Knowledge graph embedding by translating on hyperplanes
Zhen Wang, Jianwen Zhang, Jianlin Feng, and Zheng Chen. 2014 · 2014
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A compositional and interpretable semantic space
Alona Fyshe, Leila Wehbe, Partha P. Talukdar, Brian Murphy, and Tom M. Mitchell. 2015 · 2015
Cited alongside, same era.
Fast rule mining in ontological knowledge bases with AMIE+
Luis Antonio Galárraga, Christina Teflioudi, Katja Hose, and Fabian M. Suchanek. 2015 · 2015
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Semantically smooth knowledge graph embedding
Shu Guo, Quan Wang, Bin Wang, Lihong Wang, and Li Guo. 2015 · 2015
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Knowledge graph embedding via dynamic mapping matrix
Guoliang Ji, Shizhu He, Liheng Xu, Kang Liu, and Jun Zhao. 2015 · 2015
Cited alongside, same era.
Deriving Boolean structures from distributional vectors
German Kruszewski, Denis Paperno, and Marco Baroni. 2015 · 2015
Cited alongside, same era.
DBpedia: A large-scale, multilingual knowledge base extracted from Wikipedia
Jens Lehmann, Robert Isele, Max Jakob, Anja Jentzsch, Dimitris Kontokostas, Pablo N. Mendes, Sebastian Hellmann, Mohamed Morsey, Patrick van Kleef, Sören Auer, et al. 2015 · 2015
Aligning knowledge and text embeddings by entity descriptions
Huaping Zhong, Jianwen Zhang, Zhen Wang, Hai Wan, and Zheng Chen. 2015 · 2015
Later among the works it cites.
Lifted rule injection for relation embeddings
Thomas Demeester, Tim Rocktäschel, and Sebastian Riedel. 2016 · 2016
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Jointly embedding knowledge graphs and logical rules
Shu Guo, Quan Wang, Lihong Wang, Bin Wang, and Li Guo. 2016 · 2016
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TransG: A generative model for knowledge graph embedding
Han Xiao, Minlie Huang, and Xiaoyan Zhu. 2016 · 2016
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Knowledge base completion: Baselines strike back
Rudolf Kadlec, Ondrej Bajgar, and Jan Kleindienst. 2017 · 2017
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Analogical inference for multi-relational embeddings
Hanxiao Liu, Yuexin Wu, and Yiming Yang. 2017 · 2017
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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. 2015a · 2015
Cited alongside, same era.
Online learning of interpretable word embeddings
Hongyin Luo, Zhiyuan Liu, Huanbo Luan, and Maosong Sun. 2015a · 2015
Cited alongside, same era.
Context-dependent knowledge graph embedding
Yuanfei Luo, Quan Wang, Bin Wang, and Li Guo. 2015b · 2015
Cited alongside, same era.
Compositional vector space models for knowledge base completion
Arvind Neelakantan, Benjamin Roth, and Andrew McCallum. 2015 · 2015
Cited alongside, same era.
Injecting logical background knowledge into embeddings for relation extraction
Tim Rocktäschel, Sameer Singh, and Sebastian Riedel. 2015 · 2015
Cited alongside, same era.
Knowledge base completion using embeddings and rules
Quan Wang, Bin Wang, and Li Guo. 2015 · 2015
Cited alongside, same era.
Modeling relational data with graph convolutional networks
Michael Schlichtkrull, Thomas N. Kipf, Peter Bloem, Rianne van den Berg, Ivan Titov, and Max Welling. 2017 · 2017
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ProjE: Embedding projection for knowledge graph completion
Baoxu Shi and Tim Weninger. 2017 · 2017
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Knowledge graph embedding: A survey of approaches and applications
Quan Wang, Zhendong Mao, Bin Wang, and Li Guo. 2017 · 2017
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SSP: Semantic space projection for knowledge graph embedding with text descriptions
Han Xiao, Minlie Huang, and Xiaoyan Zhu. 2017 · 2017
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Leveraging knowledge bases in LSTMs for improving machine reading
Bishan Yang and Tom Mitchell. 2017 · 2017
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Convolutional 2D knowledge graph embeddings
Tim Dettmers, Minervini Pasquale, Stenetorp Pontus, and Sebastian Riedel. 2018 · 2018
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Knowledge graph embedding with iterative guidance from soft rules
Shu Guo, Quan Wang, Lihong Wang, Bin Wang, and Li Guo. 2018 · 2018
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Complex embeddings for simple link prediction
Théo Trouillon, Johannes Welbl, Sebastian Riedel, Eric Gaussier, and Guillaume Bouchard. 2016 · 2080
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