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Neural embedding-based machine learning models have shown promise for predicting novel links in knowledge graphs.
A k-nearest neighbor classification rule based on dempster-shafer theory
T. Denoeux · 1995
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On the resemblance and containment of documents
Andrei Zary Broder · 1997
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Reinforced anytime bottom up rule learning for knowledge graph completion
Christian Meilicke, Melisachew Wudage Chekol, Manuel Fink, and Heiner Stuckenschmidt · 2004
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Problog: A probabilistic prolog and its application in link discovery
Luc De Raedt, Angelika Kimmig, and Hannu Toivonen · 2007
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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 Garcia-Duran, Jason Weston, and Oksana Yakhnenko · 2013
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Quickfoil: Scalable inductive logic programming
Qiang Zeng, Jignesh M Patel, and David Page · 2014
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Fast rule mining in ontological knowledge bases with amie+
Luis Galárraga, Christina Teflioudi, Katja Hose, and Fabian M. Suchanek · 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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Embedding entities and relations for learning and inference in knowledge bases
Bishan Yang, Scott Wen-tau Yih, Xiaodong He, Jianfeng Gao, and Li Deng · 2015
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Complex embeddings for simple link prediction
Théo Trouillon, Johannes Welbl, Sebastian Riedel, Eric Gaussier, and Guillaume Bouchard · 2016
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Differentiable learning of logical rules for knowledge base reasoning
Fan Yang, Zhilin Yang, and William W. Cohen · 2017
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Convolutional 2d knowledge graph embeddings
Tim Dettmers, Pasquale Minervini, Pontus Stenetorp, and Sebastian Riedel · 2018
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Fine-grained evaluation of rule- and embedding-based systems for knowledge graph completion
Christian Meilicke, Manuel Fink, Yanjie Wang, Daniel Ruffinelli, Rainer Gemulla, and Heiner Stuckenschmidt · 2018
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Scalable rule learning via learning representation
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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Interaction embeddings for prediction and explanation in knowledge graphs
Wen Zhang, Bibek Paudel, Wei Zhang, Abraham Bernstein, and Huajun Chen · 2019
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Application of concepts of neighbours to and knowledge graph completion
Sébastien Ferré · 2020
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Markov logic networks for knowledge base completion: A theoretical analysis under the mcar assumption
Ondřej Kuželka and Jesse Davis · 2020
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Fast and exact rule mining with amie 3
Jonathan Lajus, Luis Galárraga, and Fabian Suchanek · 2020
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You can teach an old dog new tricks! on training knowledge graph embeddings
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Pouya Ghiasnezhad Omran, Kewen Wang, and Zhe Wang · 2018
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TuckER: Tensor factorization for knowledge graph completion
Ivana Balazevic, Carl Allen, and Timothy Hospedales · 2019
Cited alongside, same era.
Anytime bottom-up rule learning for knowledge graph completion
Christian Meilicke, Melisachew Wudage Chekol, Daniel Ruffinelli, and Heiner Stuckenschmidt · 2019
Cited alongside, same era.
Drum: End-to-end differentiable rule mining on knowledge graphs
Ali Sadeghian, Mohammadreza Armandpour, Patrick Ding, and Daisy Zhe Wang · 2019
Cited alongside, same era.
Building rule hierarchies for efficient logical rule learning from knowledge graphs, 2020a
Yulong Gu, Yu Guan, and Paolo Missier
Cited in the paper.
Towards learning instantiated logical rules from knowledge graphs, 2020b
Yulong Gu, Yu Guan, and Paolo Missier
Cited in the paper.
Daniel Ruffinelli, Samuel Broscheit, and Rainer Gemulla · 2020
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Learning hierarchy-aware knowledge graph embeddings for link prediction
Zhanqiu Zhang, Jianyu Cai, Yongdong Zhang, and Jie Wang · 2020
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Knowledge graph embedding for link prediction: A comparative analysis
Andrea Rossi, Denilson Barbosa, Donatella Firmani, Antonio Matinata, and Paolo Merialdo · 2021
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