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Knowledge graph (KG) reasoning is becoming increasingly popular in both academia and industry.
OWL-Eu: Adding Customised Datatypes into OWL
Jeff Z. Pan and Ian Horrocks · 2006
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Description logic rules
Markus Krötzsch, S. Rudolph, and P. Hitzler · 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 Garcia-Duran, Jason Weston, and Oksana Yakhnenko · 2013
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Programming with personalized pagerank: a locally groundable first-order probabilistic logic
William Yang Wang, Kathryn Mazaitis, and William W. Cohen · 2013
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Typed tensor decomposition of knowledge bases for relation extraction
K. Chang, W. Yih, B. Yang, and C. Meek · 2014
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Hermit: An OWL 2 reasoner
Birte Glimm, Ian Horrocks, Boris Motik, Giorgos Stoilos, and Zhe Wang · 2014
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Fast rule mining in ontological knowledge bases with AMIE+
L. Galárraga, C. Teflioudi, K. Hose, and F. M. Suchanek · 2015
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Traversing knowledge graphs in vector space
K. Guu, J. Miller, and P. Liang · 2015
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Modeling relation paths for representation learning of knowledge bases
Y. Lin, Z. Liu, H. Luan, M. Sun, S. Rao, and S. Liu · 2015
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Rdfox: A highly-scalable RDF store
Yavor Nenov, Robert Piro, Boris Motik, Ian Horrocks, Zhe Wu, and Jay Banerjee · 2015
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Knowledge base completion using embeddings and rules
Q. Wang, B. Wang, and L. Guo · 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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Structured embedding via pairwise relations and long-range interactions in knowledge base
Fei Wu, Jun Song, Yi Yang, Xi Li, Zhongfei (Mark) Zhang, and Yueting Zhuang · 2015
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Embedding entities and relations for learning and inference in knowledge bases
B. Yang, W. Yih, X. He, J. Gao, and L. Deng · 2015
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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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Complex embeddings for simple link prediction
T. Trouillon, J. Welbl, S. Riedel, E., and G. Bouchard · 2016
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Learning first-order logic embeddings via matrix factorization
William Y. Wang and William W. Cohen · 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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Regularizing knowledge graph embeddings via equivalence and inversion axioms
P. Minervini, L. Costabello, E., V., and P. Vandenbussche · 2017
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End-to-end differentiable proving
T. Rocktäschel and S. Riedel · 2017
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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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Knowledge graph embedding with diversity of structures
Wen Zhang · 2017
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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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Knowledge graph embedding with iterative guidance from soft rules
Shu Guo, Quan Wang, Lihong Wang, Bin Wang, and Li Guo · 2018
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Embedding logical queries on knowledge graphs
W. L. Hamilton, P. Bajaj, M. Zitnik, D. Jurafsky, and JJ.ure Leskovec · 2018
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Rule learning from knowledge graphs guided by embedding models
Vinh Thinh Ho, Daria Stepanova, Mohamed H. Gad-Elrab, Evgeny Kharlamov, and Gerhard Weikum · 2018
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Rule-guided compositional representation learning on knowledge graphs
Guanglin Niu, Yongfei Zhang, Bo Li, Peng Cui, Si Liu, Jingyang Li, and Xiaowei Zhang · 2020
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Beta embeddings for multi-hop logical reasoning in knowledge graphs
Hongyu Ren 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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Differentiable learning of numerical rules in knowledge graphs
Po-Wei Wang, Daria Stepanova, Csaba Domokos, and J. Zico Kolter · 2020
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Schema Aware Iterative Knowledge Graph Completion
Kemas Wiharja, Jeff Z. Pan, Martin J. Kollingbaum, and Yu Deng · 2020
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Transrhs: A representation learning method for knowledge graphs with relation hierarchical structure
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Type-sensitive knowledge base inference without explicit type supervision
Prachi Jain, Pankaj Kumar, Mausam, and Soumen Chakrabarti · 2018
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Scalable rule learning via learning representation
Pouya Ghiasnezhad Omran, Kewen Wang, and Zhe Wang · 2018
Cited alongside, same era.
Label-free distant supervision for relation extraction via knowledge graph embedding
G. Wang, W. Zhang, R. Wang, Y. Zhou, X. Chen, W. Zhang, H. Zhu, and H. Chen · 2018
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Embedding knowledge graphs based on transitivity and asymmetry of rules
M. Wang, E. Rong, H. Zhuo, and H. Zhu · 2018
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Knowledge graph embedding with hierarchical relation structure
Zhao Zhang, Fuzhen Zhuang, Meng Qu, Fen Lin, and Qing He · 2018
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Anytime bottom-up rule learning for knowledge graph completion
C. Meilicke, M. Chekol, D. Ruffinelli, and H. Stuckenschmidt · 2019
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Fuxiang Zhang, Xin Wang, Zhao Li, and Jianxin Li · 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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Complex query answering with neural link predictors
Erik Arakelyan, Daniel Daza, Pasquale Minervini, and Michael Cochez · 2021
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Low-resource learning with knowledge graphs: A comprehensive survey
Jiaoyan Chen, Yuxia Geng, Zhuo Chen, Jeff Z Pan, Yuan He, Wen Zhang, and so on · 2021
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Injecting background knowledge into embedding models for predictive tasks on knowledge graphs
Claudia d’Amato, Nicola Flavio Quatraro, and Nicola Fanizzi · 2021
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Ontozsl: Ontology-enhanced zero-shot learning
Yuxia Geng, Jiaoyan Chen, Zhuo Chen, Jeff Z. Pan, Zhiquan Ye, Zonggang Yuan, Yantao Jia, and Huajun Chen · 2021
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Improving knowledge graph embeddings with ontological reasoning
N. Jain, T. Tran, M. H. Gad-Elrab, and D. Stepanova · 2021
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Ans. complex queries in KGs with bidirectional sequence encoders
B. Kotnis, C. Lawrence, and M. Niepert · 2021
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Neural-answering logical queries on knowledge graphs
Lihui Liu, Boxin Du, Heng Ji, ChengXiang Zhai, and Hanghang Tong · 2021
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RETA: A schema-aware, end-to-end solution for instance completion in knowledge graphs
Paolo Rosso, Dingqi Yang, Natalia Ostapuk, and Philippe Cudré-Mauroux · 2021
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Rot-pro: Modeling transitivity by projection in knowledge graph embedding
Tengwei Song, Jie Luo, and Lei Huang · 2021
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TAGAT: type-aware graph attention networks for reasoning over knowledge graphs
Yuzhuo Wang, Hongzhi Wang, Junwei He, Wenbo Lu, and Shuolin Gao · 2021
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Improving conversational recommender system by pretraining billion-scale knowledge graph
C. Wong, F. Feng, W. Zhang, C. Vong, H. Chen, Y. Zhang, P. He, H. Chen, K. Zhao, and H. Chen · 2021
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Neural, symbolic and neural-symbolic reasoning on knowledge graphs
Jing Zhang, Bo Chen, Lingxi Zhang, Xirui Ke, and Haipeng Ding · 2021
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Billion-scale pre-trained e-commerce product knowledge graph model
W. Zhang, C. Man Wong, G. Ye, B. Wen, W. Zhang, and H. Chen · 2021
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Cone: Cone embeddings for multi-hop reasoning over knowledge graphs
Z. Zhang, J. Wang, J. Chen, S. Ji, and F. Wu · 2021
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