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Multi-hop reasoning has been widely studied in recent years to seek an effective and interpretable method for knowledge graph (KG) completion.
Simple statistical gradient-following algorithms for connectionist reinforcement learning
Ronald J Williams. 1992 · 1992
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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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Toward an architecture for never-ending language learning
Andrew Carlson, Justin Betteridge, Bryan Kisiel, Burr Settles, Estevam R Hruschka, and Tom M Mitchell. 2010 · 2010
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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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Translating embeddings for modeling multi-relational data
Antoine Bordes, Nicolas Usunier, Alberto Garcia-Duran, 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 Ng. 2013 · 2013
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba. 2014 · 2014
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Wikidata: a free collaborative knowledge base
Denny Vrandečić and Markus Krötzsch. 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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Traversing knowledge graphs in vector space
Kelvin Guu, John Miller, and Percy Liang. 2015 · 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 · 2015
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Representing text for joint embedding of text and knowledge bases
Kristina Toutanova, Danqi Chen, Patrick Pantel, Hoifung Poon, Pallavi Choudhury, and Michael Gamon. 2015 · 2015
Cited alongside, same era.
Embedding entities and relations for learning and inference in knowledge bases
Bishan Yang, Wen-tau Yih, Xiaodong He, Jianfeng Gao, and Li Deng. 2015 · 2015
Cited alongside, same era.
Learning symmetric collaborative dialogue agents with dynamic knowledge graph embeddings
He He, Anusha Balakrishnan, Mihail Eric, and Percy Liang. 2017 · 2017
Cited alongside, same era.
End-to-end differentiable proving
Tim Rocktäschel and Sebastian Riedel. 2017 · 2017
Cited alongside, same era.
Knowledge graph embedding: A survey of approaches and applications
Quan Wang, Zhendong Mao, Bin Wang, and Li Guo. 2017 · 2017
Cited alongside, same era.
Deeppath: A reinforcement learning method for knowledge graph reasoning
Multi-hop knowledge graph reasoning with reward shaping
Xi Victoria Lin, Richard Socher, and Caiming Xiong. 2018 · 2018
Later among the works it cites.
A novel embedding model for knowledge base completion based on convolutional neural network
Tu Dinh Nguyen, Dat Quoc Nguyen, Dinh Phung, et al. 2018 · 2018
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M-walk: Learning to walk over graphs using monte carlo tree search
Yelong Shen, Jianshu Chen, Po-Sen Huang, Yuqing Guo, and Jianfeng Gao. 2018 · 2018
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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. 2018 · 2018
Later among the works it cites.
Tucker: Tensor factorization for knowledge graph completion
Ivana Balazevic, Carl Allen, and Timothy Hospedales. 2019 · 2019
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Collaborative policy learning for open knowledge graph reasoning
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Wenhan Xiong, Thien Hoang, and William Yang Wang. 2017 · 2017
Cited alongside, same era.
Differentiable learning of logical rules for knowledge base reasoning
Fan Yang, Zhilin Yang, and William W Cohen. 2017 · 2017
Cited alongside, same era.
Variational knowledge graph reasoning
Wenhu Chen, Wenhan Xiong, Xifeng Yan, and William Yang Wang. 2018 · 2018
Cited alongside, same era.
Go for a walk and arrive at the answer: Reasoning over paths in knowledge bases using reinforcement learning
Rajarshi Das, Shehzaad Dhuliawala, Manzil Zaheer, Luke Vilnis, Ishan Durugkar, Akshay Krishnamurthy, Alex Smola, and Andrew McCallum. 2018 · 2018
Cited alongside, same era.
Convolutional 2d knowledge graph embeddings
Tim Dettmers, Pasquale Minervini, Pontus Stenetorp, and Sebastian Riedel. 2018 · 2018
Cited alongside, same era.
Cong Fu, Tong Chen, Meng Qu, Woojeong Jin, and Xiang Ren. 2019 · 2019
Later among the works it cites.
Adapting meta knowledge graph information for multi-hop reasoning over few-shot relations
Xin Lv, Yuxian Gu, Xu Han, Lei Hou, Juanzi Li, and Zhiyuan Liu. 2019 · 2019
Later among the works it cites.
End-to-end structure-aware convolutional networks for knowledge base completion
Chao Shang, Yun Tang, Jing Huang, Jinbo Bi, Xiaodong He, and Bowen Zhou. 2019 · 2019
Later among the works it cites.
Incorporating graph attention mechanism into knowledge graph reasoning based on deep reinforcement learning
Heng Wang, Shuangyin Li, Rong Pan, and Mingzhi Mao. 2019 · 2019
Later among the works it cites.
Enhancing pre-trained language representations with rich knowledge for machine reading comprehension
An Yang, Quan Wang, Jing Liu, Kai Liu, Yajuan Lyu, Hua Wu, Qiaoqiao She, and Sujian Li. 2019 · 2019
Later among the works it cites.