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Knowledge graph embeddings are now a widely adopted approach to knowledge representation in which entities and relationships are embedded in vector spaces.
The expression of a tensor or a polyadic as a sum of products
Frank L. Hitchcock · 1927
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The logic of quantum mechanics
Garrett Birkhoff and John Von Neumann · 1936
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Dbpedia: A nucleus for a web of open data
Sören Auer, Christian Bizer, Georgi Kobilarov, Jens Lehmann, Richard Cyganiak, and Zachary Ives · 2007
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The graph neural network model
Franco Scarselli, Marco Gori, Ah Chung Tsoi, Markus Hagenbuchner, and Gabriele Monfardini · 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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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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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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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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Reasoning with neural tensor networks for knowledge base completion
Richard Socher, Danqi Chen, Christopher D Manning, and Andrew Ng · 2013
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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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Yago3: A knowledge base from multilingual wikipedias
Farzaneh Mahdisoltani, Joanna Biega, and Fabian Suchanek · 2014
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Knowledge graph and text jointly embedding
Zhen Wang, Jianwen Zhang, Jianlin Feng, and Zheng Chen · 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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Embedding entities and relations for learning and inference in knowledge bases
Bishan Yang, Wen-tau Yih, Xiaodong He, Jianfeng Gao, and Li Deng · 2014
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On approximate reasoning capabilities of low-rank vector spaces
Guillaume Bouchard, Sameer Singh, and Theo Trouillon · 2015
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Traversing knowledge graphs in vector space
Kelvin Guu, John Miller, and Percy Liang · 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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Injecting logical background knowledge into embeddings for relation extraction
Tim Rocktäschel, Sameer Singh, and Sebastian Riedel · 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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Observed versus latent features for knowledge base and text inference
Kristina Toutanova and Danqi Chen · 2015
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Learning to rank entity relatedness through embedding-based features
Pierpaolo Basile, Annalina Caputo, Gaetano Rossiello, and Giovanni Semeraro · 2016
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Lifted rule injection for relation embeddings
Thomas Demeester, Tim Rocktäschel, and Sebastian Riedel · 2016
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Towards a definition of knowledge graphs
Lisa Ehrlinger and Wolfram Wöß · 2016
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Predicting the co-evolution of event and knowledge graphs
Cristóbal Esteban, Volker Tresp, Yinchong Yang, Stephan Baier, and Denis Krompaß · 2016
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Entity disambiguation by knowledge and text jointly embedding
Wei Fang, Jianwen Zhang, Dilin Wang, Zheng Chen, and Ming Li · 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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Entity embeddings with conceptual subspaces as a basis for plausible reasoning
Shoaib Jameel and Steven Schockaert · 2016
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Encoding temporal information for time-aware link prediction
Tingsong Jiang, Tianyu Liu, Tao Ge, Lei Sha, Sujian Li, Baobao Chang, and Zhifang Sui · 2016
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Knowledge representation learning with entities, attributes and relations
Yankai Lin, Zhiyuan Liu, and Maosong Sun · 2016
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Leveraging the schema in latent factor models for knowledge graph completion
Pasquale Minervini, Claudia d’Amato, Nicola Fanizzi, and Floriana Esposito · 2016
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Holographic embeddings of knowledge graphs
Maximilian Nickel, Lorenzo Rosasco, and Tomaso Poggio · 2016
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Logic tensor networks: Deep learning and logical reasoning from data and knowledge
Luciano Serafini and Artur d’Avila Garcez · 2016
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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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Learning first-order logic embeddings via matrix factorization
William Yang Wang and William W Cohen · 2016
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Text-enhanced representation learning for knowledge graph
Zhigang Wang and Juan-Zi Li · 2016
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Representation learning of knowledge graphs with entity descriptions
Ruobing Xie, Zhiyuan Liu, Jia Jia, Huanbo Luan, and Maosong Sun · 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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Collaborative knowledge base embedding for recommender systems
Fuzheng Zhang, Nicholas Jing Yuan, Defu Lian, Xing Xie, and Wei-Ying Ma · 2016
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Improving visual relationship detection using semantic modeling of scene descriptions
Stephan Baier, Yunpu Ma, and Volker Tresp · 2017
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Chains of reasoning over entities, relations, and text using recurrent neural networks
Rajarshi Das, Arvind Neelakantan, David Belanger, and Andrew McCallum · 2017
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Logic tensor networks for semantic image interpretation
Poincar \ \backslash ’e glove: Hyperbolic word embeddings
Alexandru Tifrea, Gary Bécigneul, and Octavian-Eugen Ganea · 2018
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DKN: deep knowledge-aware network for news recommendation
Hongwei Wang, Fuzheng Zhang, Xing Xie, and Minyi Guo · 2018
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Recurrent one-hop predictions for reasoning over knowledge graphs
Wenpeng Yin, Yadollah Yaghoobzadeh, and Hinrich Schütze · 2018
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On understanding knowledge graph representation
Carl Allen, Ivana Balazevic, and Timothy M Hospedales · 2019
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Multi-relational poincar \ \backslash ’e graph embeddings
Ivana Balažević, Carl Allen, and Timothy Hospedales · 2019
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I Donadello, L Serafini, and AS d’Avila Garcez · 2017
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Alberto Garcia-Duran and Mathias Niepert · 2017
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On the equivalence of holographic and complex embeddings for link prediction
Katsuhiko Hayashi and Masashi Shimbo · 2017
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Knowledge base completion: Baselines strike back
Rudolf Kadlec, Ondrej Bajgar, and Jan Kleindienst · 2017
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Analogical inference for multi-relational embeddings
Hanxiao Liu, Yuexin Wu, and Yiming Yang · 2017
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Regularizing knowledge graph embeddings via equivalence and inversion axioms
Pasquale Minervini, Luca Costabello, Emir Muñoz, Vít Novácek, and Pierre-Yves Vandenbussche · 2017
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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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TuckER: Tensor factorization for knowledge graph completion
Ivana Balazevic, Carl Allen, and Timothy Hospedales · 2019
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Complementing logical reasoning with sub-symbolic commonsense
Federico Bianchi, Matteo Palmonari, Pascal Hitzler, and Luciano Serafini · 2019
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AmpliGraph: a Library for Representation Learning on Knowledge Graphs, March 2019
Luca Costabello, Sumit Pai, Chan Le Van, Rory McGrath, Nicholas McCarthy, and Pedro Tabacof · 2019
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Compensating supervision incompleteness with prior knowledge in semantic image interpretation
Ivan Donadello and Luciano Serafini · 2019
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Measuring social bias in knowledge graph embeddings
Joseph Fisher · 2019
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Quantum embedding of knowledge for reasoning
Dinesh Garg, Shajith Ikbal Mohamed, Santosh K Srivastava, Harit Vishwakarma, Hima Karanam, and L Venkata Subramaniam · 2019
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A survey on knowledge graph embeddings with literals: Which model links better literal-ly?
Genet Asefa Gesese, Russa Biswas, Mehwish Alam, and Harald Sack · 2019
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Care: Open knowledge graph embeddings
Swapnil Gupta, Sreyash Kenkre, and Partha Talukdar · 2019
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Neural-symbolic integration and the semantic web
Pascal Hitzler, Federico Bianchi, Monireh Ebrahimi, and Md Kamruzzaman Sarker · 2019
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Hyperkg: Hyperbolic knowledge graph embeddings for knowledge base completion
Prodromos Kolyvakis, Alexandros Kalousis, and Dimitris Kiritsis · 2019
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Inferring concept hierarchies from text corpora via hyperbolic embeddings
Matt Le, Stephen Roller, Laetitia Papaxanthos, Douwe Kiela, and Maximilian Nickel · 2019
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On the role of knowledge graphs in explainable ai
Freddy Lecue · 2019
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PyTorch-BigGraph: A Large-scale Graph Embedding System
Adam Lerer, Ledell Wu, Jiajun Shen, Timothee Lacroix, Luca Wehrstedt, Abhijit Bose, and Alex Peysakhovich · 2019
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Mmkg: Multi-modal knowledge graphs
Ye Liu, Hui Li, Alberto Garcia-Duran, Mathias Niepert, Daniel Onoro-Rubio, and David S Rosenblum · 2019
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Opendialkg: Explainable conversational reasoning with attention-based walks over knowledge graphs
Seungwhan Moon, Pararth Shah, Anuj Kumar, and Rajen Subba · 2019
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Investigating robustness and interpretability of link prediction via adversarial modifications
Pouya Pezeshkpour, CA Irvine, Yifan Tian, and Sameer Singh · 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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Hyperbolic disk embeddings for directed acyclic graphs
Ryota Suzuki, Ryusuke Takahama, and Shun Onoda · 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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Mapping lexical knowledge to distributed models for ontology concept invention
Manuel Vimercati, Federico Bianchi, Mauricio Soto, and Matteo Palmonari · 2019
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Explainable reasoning over knowledge graphs for recommendation
Xiang Wang, Dingxian Wang, Canran Xu, Xiangnan He, Yixin Cao, and Tat-Seng Chua · 2019
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Multimodal data enhanced representation learning for knowledge graphs
Zikang Wang, Linjing Li, Qiudan Li, and Daniel Zeng · 2019
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Gnnexplainer: Generating explanations for graph neural networks
Zhitao Ying, Dylan Bourgeois, Jiaxuan You, Marinka Zitnik, and Jure Leskovec · 2019
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Learning hierarchy-aware knowledge graph embeddings for link prediction
Zhanqiu Zhang, Jianyu Cai, Yongdong Zhang, and Jie Wang · 2019
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Knowledge graphs, 2020
Aidan Hogan, Eva Blomqvist, Michael Cochez, Claudia d’Amato, Gerard de Melo, Claudio Gutierrez, José Emilio Labra Gayo, Sabrina Kirrane, Sebastian Neumaier, Axel Polleres, Roberto Navigli, Axel-Cyrille Ngonga Ngomo, Sabbir M. Rashid, Anisa Rula, Lukas Schmelzeisen, Juan Sequeda, Steffen Staab, and Antoine Zimmermann · 2020
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Differentiable reasoning on large knowledge bases and natural language
Pasquale Minervini, Matko Bošnjak, Tim Rocktäschel, Sebastian Riedel, and Edward Grefenstette · 2020
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Query2box: Reasoning over knowledge graphs in vector space using box embeddings
Hongyu Ren, Weihua Hu, and Jure Leskovec · 2020
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Query2box: Reasoning over knowledge graphs in vector space using box embeddings
Hongyu Ren*, Weihua Hu*, and Jure Leskovec · 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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Probability Calibration for Knowledge Graph Embedding Models
Pedro Tabacof and Luca Costabello · 2020
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