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Knowledge base completion (KBC) aims to automatically infer missing facts by exploiting information already present in a knowledge base (KB).
The expression of a tensor or a polyadic as a sum of products
Frank L Hitchcock · 1927
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Some mathematical notes on three-mode factor analysis
Ledyard R Tucker · 1966
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On the Boxicity and Cubicity of a graph
Fred S. Roberts · 1968
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Freebase: A shared database of structured general human knowledge
Kurt D. Bollacker, Robert P. Cook, and Patrick Tufts · 2007
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Geometric representation of graphs in low dimension using axis parallel boxes
L. Sunil Chandran, Mathew C. Francis, and Naveen Sivadasan · 2008
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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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Translating embeddings for modeling multi-relational data
Antoine Bordes, Nicolas Usunier, Alberto García-Durán, 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 Y. Ng · 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
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Question answering with subgraph embeddings
Antoine Bordes, Sumit Chopra, and Jason Weston · 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
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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
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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 base completion via search-based question answering
Robert West, Evgeniy Gabrilovich, Kevin Murphy, Shaohua Sun, Rahul Gupta, and Dekang Lin · 2014
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Adam: A method for stochastic optimization
Diederik Kingma and Jimmy Ba · 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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YAGO3: A knowledge base from multilingual wikipedias
Farzaneh Mahdisoltani, Joanna Biega, and Fabian M. Suchanek · 2015
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Injecting logical background knowledge into embeddings for relation extraction
Tim Rocktäschel, Sameer Singh, and Sebastian Riedel · 2015
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Embedding entities and relations for learning and inference in knowledge bases
Bishan Yang, Wen-tau Yih, Xiaodong He, Jianfeng Gao, and Li Deng · 2015
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Lifted rule injection for relation embeddings
Thomas Demeester, Tim Rocktäschel, and Sebastian Riedel · 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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Knowledge graph completion with adaptive sparse transfer matrix
Guoliang Ji, Kang Liu, Shizhu He, and Jun Zhao · 2016
Canonical tensor decomposition for knowledge base completion
Timothée Lacroix, Nicolas Usunier, and Guillaume Obozinski · 2018
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Differentiating concepts and instances for knowledge graph embedding
Xin Lv, Lei Hou, Juanzi Li, and Zhiyuan Liu · 2018
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Never-ending learning
Tom M. Mitchell, William W. Cohen, Estevam R. Hruschka Jr., Partha P. Talukdar, Bo Yang, Justin Betteridge, Andrew Carlson, Bhavana Dalvi Mishra, Matt Gardner, Bryan Kisiel, Jayant Krishnamurthy, Ni Lao, Kathryn Mazaitis, Thahir Mohamed, Ndapandula Nakashole, Emmanouil A. Platanios, Alan Ritter, Mehdi Samadi, Burr Settles, Richard C. Wang, Derry Wijaya, Abhinav Gupta, Xinlei Chen, Abulhair Saparov, Malcolm Greaves, and Joel Welling · 2018
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New embedded representations and evaluation protocols for inferring transitive relations
Sandeep Subramanian and Soumen Chakrabarti · 2018
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Probabilistic Embedding of Knowledge Graphs with Box Lattice Measures
Luke Vilnis, Xiang Li, Shikhar Murty, and Andrew McCallum · 2018
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Complex embeddings for simple link prediction
Théo Trouillon, Johannes Welbl, Sebastian Riedel, Éric Gaussier, and Guillaume Bouchard · 2016
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On the Representation and Embedding of Knowledge Bases beyond Binary Relations
Jianfeng Wen, Jianxin Li, Yongyi Mao, Shini Chen, and Richong Zhang · 2016
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Representation learning of knowledge graphs with hierarchical types
Ruobing Xie, Zhiyuan Liu, and Maosong Sun · 2016
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Adversarial sets for regularising neural link predictors
Pasquale Minervini, Thomas Demeester, Tim Rocktäschel, and Sebastian Riedel · 2017
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Explicit semantic ranking for academic search via knowledge graph embedding
Chenyan Xiong, Russell Power, and Jamie Callan · 2017
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Leveraging knowledge bases in LSTMs for improving machine reading
Bishan Yang and Tom M. Mitchell · 2017
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Ripplenet: Propagating user preferences on the knowledge graph for recommender systems
Hongwei Wang, Fuzheng Zhang, Jialin Wang, Miao Zhao, Wenjie Li, Xing Xie, and Minyi Guo · 2018
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TuckER: Tensor factorization for knowledge graph completion
Ivana Balazevic, Carl Allen, and Timothy M. Hospedales · 2019
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Knowledge hypergraphs: Extending knowledge graphs beyond binary relations
Bahare Fatemi, Perouz Taslakian, David Vázquez, and David Poole · 2019
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Smoothing the geometry of probabilistic box embeddings
Xiang Li, Luke Vilnis, Dongxu Zhang, Michael Boratko, and Andrew McCallum · 2019
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Learning attention-based embeddings for relation prediction in knowledge graphs
Deepak Nathani, Jatin Chauhan, Charu Sharma, and Manohar Kaul · 2019
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RotatE: Knowledge graph embedding by relational rotation in complex space
Zhiqing Sun, Zhi-Hong Deng, Jian-Yun Nie, and Jian Tang · 2019
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On inductive abilities of latent factor models for relational learning
Théo Trouillon, Éric Gaussier, Christopher R. Dance, and Guillaume Bouchard · 2019
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Query2box: Reasoning over knowledge graphs in vector space using box embeddings
Jure Leskovec Hongyu Ren, Weihua Hu · 2020
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Self-supervised learning
Yann LeCun · 2020
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Generalizing tensor decomposition for n-ary relational knowledge bases
Yu Liu, Quanming Yao, and Yong Li · 2020
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You CAN teach an old dog new tricks! On training knowledge graph embeddings
Daniel Ruffinelli, Samuel Broscheit, and Rainer Gemulla · 2020
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