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KGE

Some papers on Knowledge Graph Embedding(KGE)

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Contents

Libraries

Methodologies

Traditions

Translation

Year Source Methods
2013 NeurIPS TransE
2014 AAAI TransH
2015 AAAI TransR
2015 ACL TransD
2015 EMNLP PTransE
2015 EMNLP RTransE
2015 CIKM KG2E
2016 AAAI TransA
2016 AAAI TranSparse
2016 IJCAI ManifoldE
2016 ACL TransG
2016 KR FTransE
2016 NAACL-HLT lppTransE
2016 NAACL-HLT STransE
2017 AAAI puTransE
2017 ACL ITransF
2017 CIKM TransE-RS
2017 CIKM CombinE
2018 AAAI TorusE
2018 AAAI TransAt
2018 EMNLP TransC
2019 ICLR RotatE
2019 AAAI TransGate
2019 IJCAI TransMS
2019 WSDM CrossE
2020 AAAI HAKE

Multiplication

Year Source Methods
2011 ICML RESCAL
2015 ICLR DistMult
2016 ICML ComplEx
2016 AAAI HolE
2017 ICML ANALOGY
2018 NeurIPS SimplE
2019 ACL DihEdral
2019 EMNLP TuckER

Neural Networks

Year Source Methods
2013 NeurIPS NTN
2014 KDD ER-MLP
2017 AAAI ProjE
2018 AAAI ConvE
2018 CIKM SENN
2018 ESWC R-GCN
2018 NAACL-HLT ConvKB
2018 NAACL-HLT KBGAN
2019 ICML RSN
2019 AAAI SACN
2019 IJCAI VR-GCN
2019 IJCAI M-GNN
2019 ACL KBGAT
2019 WWW ActiveLink
2019 NAACL-HLT CapsE
2019 NAACL-HLT ConvR
2019 K-CAP TransGCN
2020 ICLR CompGCN
2020 ICLR DPMPN
2020 AAAI InteractE

Informations

Path

Year Source Methods
2015 EMNLP PTransE
2015 EMNLP RTransE
2015 EMNLP TransE-COMP
2016 COLING GAKE
2017 EMNLP DeepPath
2017 CIKM TCE
2018 ICLR MINERVA
2018 EMNLP MultiHopKG
2019 ICML RSN
2019 EMNLP OPTransE
2020 AAAI RPJE

Textual

Year Source Methods
2014 EMNLP pTransE
2015 EMNLP Jointly(desp)
2016 AAAI DKRL
2016 IJCAI TEKE
2017 AAAI SSP
2017 IJCAI Jointly(A-LSTM)
2017 ACL FRN
2018 AAAI ConMask
2018 AAAI JointNRE
2018 NAACL-HLT ATE
2019 AAAI OWE
2019 IJCAI WWV
2019 EMNLP CaRe
2019 EMNLP TCVAE
2019 EMNLP CPL

Hierarchy

Year Source Methods
2016 IJCAI TKRL
2016 SIGIR HiRi
2018 AAAI TransE-T
2018 EMNLP TransE-HRS
2020 AAAI HAKE

Taxonomic

Year Source Methods
2019 AAAI SimplE+

Neighborhood

Year Source Methods
2016 NeurIPS Gaifman
2016 COLING GAKE
2017 CIKM TCE
2018 UAI KBLRN
2018 CIKM SENN
2018 ESWC R-GCN
2019 AAAI LENA
2019 AAAI LAN
2019 AAAI SACN
2019 WWW TransN
2019 EMNLP CaRe
2020 AAAI FSRL

Augmentations

Constraints

Year Source Methods
2015 ACL SSE
2018 ACL ComplEx-NNE
2019 AAAI SimplE+

Regularizers

Year Source Methods
2015 ACL SSE
2018 ICML ComplEx-N3
2018 AAAI ComplEx-L1
2019 UAI EM
2020 ICLR Teach

Soft Rules

Year Source Methods
2015 IJCAI r-TransE
2016 IJCAI ProPPR
2016 EMNLP KALE
2017 NeurIPS Neural-LP
2018 NeurIPS GQE
2018 AAAI RUGE
2019 NeurIPS DRUM
2019 AAAI UKGE
2019 IJCAI AnyBURL
2019 WWW IterE
2020 ICLR Neural-LP-N
2020 ICLR Q2B
2020 AAAI RPJE

Negative Sampling

Year Source Methods
2014 AAAI TransH
2018 AAAI IGAN
2018 NAACL-HLT KBGAN
2019 ICLR RotatE
2019 ICDE NSCaching

Emergents

Few Shot

Year Source Methods
2018 EMNLP GMatching
2019 EMNLP MetaR
2019 EMNLP TCVAE
2019 EMNLP Meta-KGR
2020 NeurIPS GEN
2020 AAAI FSRL
2020 AAAI ZSGAN
2020 EMNLP FAAN
2020 EMNLP FIRE

Hyper Planes

Year Source Methods
2016 ICML ComplEx
2018 AAAI TorusE
2019 NeurIPS QuatE
2019 NeurIPS MuRP
2019 ICLR RotatE
2020 AAAI HAKE

Graph Networks

Year Source Methods
2018 ESWC R-GCN
2019 AAAI SACN
2019 IJCAI VR-GCN
2019 ICASSP GRNN
2019 PRICAI SAGCN
2019 K-CAP TransGCN
2020 IEEE Access GAATs
2020 ICLR CompGCN
2020 ICLR DPMPN
2020 AAAI RGHAT
2020 CoRR TGCN

Temporal

Year Source Methods
2014 EMNLP CTPs
2016 EMNLP t-TransE
2016 COLING TransE-TAE
2017 ICML Know-Evolve
2017 AAAI MLNs
2018 WWW TTransE
2018 EMNLP TA-DistMult
2018 EMNLP HyTE
2019 Journal of Web Semantics ConT
2019 ICLR DyRep
2019 ICTAI Hybrid-TE
2019 WISE CATE
2020 IEEE Access TDG2E
2020 ICLR TComplEx
2020 AAAI DE-SimplE
2020 IJCAI DArtNet
2020 CoRR TIMEPLEX

Papers

Survey

  • Yoshua Bengio, Aaron C. Courville, Pascal Vincent. "Representation Learning: A Review and New Perspectives". Transactions on Pattern Analysis and Machine Intelligence 2013. paper

  • Maximilian Nickel, Kevin Murphy, Volker Tresp, Evgeniy Gabrilovich. "A Review of Relational Machine Learning for Knowledge Graphs". Proceedings of the IEEE 2016. paper

  • Quan Wang, Zhendong Mao, Bin Wang, Li Guo. "Knowledge Graph Embedding: A Survey of Approaches and Applications". IEEE Transactions on Knowledge and Data Engineering 2017. paper

  • HongYun Cai, Vincent W. Zheng, Kevin Chen-Chuan Chang. "A Comprehensive Survey of Graph Embedding: Problems, Techniques, and Applications". IEEE Transactions on Knowledge and Data Engineering 2018. paper

  • Xiaojun Chen, Shengbin Jia, Yang Xiang. "A review: Knowledge reasoning over knowledge graph". Expert Systems with Applications 2020. paper

  • Seyed Mehran Kazemi, Rishab Goel, Kshitij Jain, Ivan Kobyzev, Akshay Sethi, Peter Forsyth, Pascal Poupart. "Relational Representation Learning for Dynamic (Knowledge) Graphs: A Survey". arxiv 2019-05. paper

  • Shaoxiong Ji, Shirui Pan, Erik Cambria, Pekka Marttinen, Philip S. Yu. "A Survey on Knowledge Graphs: Representation, Acquisition and Applications". arxiv 2020-02. paper

  • Andrea Rossi, Donatella Firmani, Antonio Matinata, Paolo Merialdo, Denilson Barbosa. "Knowledge Graph Embedding for Link Prediction: A Comparative Analysis". arxiv 2020-02. paper

2011

Conference

  • (RESCAL) Nickel Maximilian, Tresp Volker, Kriegel Hans-Peter. "A Three-Way Model for Collective Learning on Multi-Relational Data". ICML 2011. CCF A. Cite 1114. paper code 🔥

  • (SE) Antoine Bordes, Jason Weston, Ronan Collobert, Yoshua Bengio. "Learning Structured Embeddings of Knowledge Bases". AAAI 2011. CCF A. Cite 743. paper 🔥

2012

Conference

  • (LFM) Rodolphe Jenatton, Nicolas L. Roux, Antoine Bordes, Guillaume R. Obozinski. "A Latent Factor Model for Highly Multi-relational Data". NIPS 2012. CCF A. Cite 371. paper 🔥

2013

Conference

  • (TransE) Antoine Bordes, Nicolas Usunier, Alberto Garcia-Duran, Jason Weston, Oksana Yakhnenko. "Translating Embeddings for Modeling Multi-relational Data". NIPS 2013. CCF A. Cite 2679. paper reviews 🔥

  • (SLM/NTN) Richard Socher, Danqi Chen, Christopher D. Manning, Andrew Y. Ng. "Reasoning With Neural Tensor Networks for Knowledge Base Completion". NIPS 2013. CCF A. Cite 1414. paper reviews 🔥

2014

Conference

  • (TransH) Zhen Wang, Jianwen Zhang, Jianlin Feng, Zheng Chen. "Knowledge Graph Embedding by Translating on Hyperplanes". AAAI 2014. CCF A. Cite 1333. paper 🔥

  • (ER-MLP) Xin Dong, Evgeniy Gabrilovich, Geremy Heitz, Wilko Horn, Ni Lao, Kevin Murphy, Thomas Strohmann, Shaohua Sun, Wei Zhang. "Knowledge vault: a web-scale approach to probabilistic knowledge fusion". KDD 2014. CCF A. Cite 1302. paper 🔥

  • (pTransE) Zhen Wang, Jianwen Zhang, Jianlin Feng, Zheng Chen. "Knowledge Graph and Text Jointly Embedding". EMNLP 2014. CCF B. Cite 311. paper 🔥

  • (CTPs) Derry Tanti Wijaya, Ndapandula Nakashole, Tom M. Mitchell. "CTPs: Contextual Temporal Profiles for Time Scoping Facts using State Change Detection". EMNLP 2014. CCF B. Cite 6. paper

2015

Conference

  • (DistMult) Bishan Yang, Wen-tau Yih, Xiaodong He, Jianfeng Gao, Li Deng. "Embedding Entities and Relations for Learning and Inference in Knowledge Bases". ICLR 2015. CCF A. Cite 870. paper 🔥

  • (TransR/CTransR) Yankai Lin, Zhiyuan Liu, Maosong Sun, Yang Liu, Xuan Zhu. "Learning Entity and Relation Embeddings for Knowledge Graph Completion". AAAI 2015. CCF A. Cite 498?. paper code 🔥

  • (TransD) Guoliang Ji, Shizhu He, Liheng Xu, Kang Liu, Jun Zhao. "Knowledge Graph Embedding via Dynamic Mapping Matrix". ACL 2015. CCF A. Cite 615. paper 🔥

  • (r-TransE) Quan Wang, Bin Wang, Li Guo. "Knowledge Base Completion Using Embeddings and Rules". IJCAI 2015. CCF A. Cite 138. paper 🔥

  • (SSE) Shu Guo, Quan Wang, Bin Wang, Lihong Wang, Li Guo. "Semantically Smooth Knowledge Graph Embedding". ACL 2015. CCF A. Cite 98. paper 🔥

  • (AMDC) Hiroshi Kajino, Akihiro Kishimoto, Adi Botea, Elizabeth M. Daly, Spyros Kotoulas. "Active Learning for Multi-relational Data Construction". WWW 2015. CCF A. Cite 5. paper

  • (PTransE) Yankai Lin, Zhiyuan Liu, Huanbo Luan, Maosong Sun, Siwei Rao, Song Liu. "Modeling Relation Paths for Representation Learning of Knowledge Bases". EMNLP 2015. CCF B. Cite 368. paper code 🔥

  • (TransE-COMP) Kelvin Guu, John Miller, Percy Liang. "Traversing Knowledge Graphs in Vector Space". EMNLP 2015. CCF B. Cite 242. paper code 🔥

  • (Jointly(desp)) Huaping Zhong, Jianwen Zhang, Zhen Wang, Hai Wan, Zheng Chen. "Aligning Knowledge and Text Embeddings by Entity Descriptions". EMNLP 2015. CCF B. Cite 109. paper 🔥

  • (RTransE) Alberto Garcia-Duran, Antoine Bordes, Nicolas Usunier. "Composing Relationships with Translations". EMNLP 2015. CCF B. Cite 77. paper

  • Yuanfei Luo, Quan Wang, Bin Wang, Li Guo. "Context-Dependent Knowledge Graph Embedding". EMNLP 2015. CCF B.Cite 39. paper

  • (KG2E) Shizhu He, Kang Liu, Guoliang Ji, Jun Zhao. "Learning to Represent Knowledge Graphs with Gaussian Embedding". CIKM 2015. CCF B. Cite 189. paper 🔥

  • Zhuoyu Wei, Jun Zhao, Kang Liu, Zhenyu Qi, Zhengya Sun, Guanhua Tian. "Large-scale Knowledge Base Completion: Inferring via Grounding Network Sampling over Selected Instances". CIKM 2015. CCF B. Cite 40. paper

2016

Journal

  • Fei Tian, Bin Gao, Enhong Chen, Tie-Yan Liu. "Learning Better Word Embedding by Asymmetric Low-Rank Projection of Knowledge Graph". Journal of Computer Science and Technology 2016. Sci 3. Impact 1.506. Cite 9. paper

  • Pasquale Minervini, Claudia d'Amato, Nicola Fanizzi. "Efficient energy-based embedding models for link prediction in knowledge graphs". Journal of Intelligent Information Systems 2016. Sci 4. Impact 1.813. Cite 9. paper

Conference

  • (Gaifman) Mathias Niepert. "Discriminative Gaifman Models". NeurIPS 2016. CCF A. Cite 29. paper reviews

  • (ComplEx) Théo Trouillon, Johannes Welbl, Sebastian Riedel, Éric Gaussier, Guillaume Bouchard. "Complex Embeddings for Simple Link Prediction". ICML 2016. CCF A. Cite 739. paper code 🔥 💥

  • (HolE) Maximilian Nickel, Lorenzo Rosasco, Tomaso Poggio. "Holographic Embeddings of Knowledge Graphs". AAAI 2016. CCF A. Cite 577. paper code 🔥 💥

  • (DKRL) Ruobing Xie, Zhiyuan Liu, Jia Jia, Huanbo Luan, Maosong Sun. "Representation Learning of Knowledge Graphs with Entity Descriptions". AAAI 2016. CCF A. Cite 317. paper code 🔥 💥

  • (TranSparse) Guoliang Ji, Kang Liu, Shizhu He, Jun Zhao. "Knowledge Graph Completion with Adaptive Sparse Transfer Matrix". AAAI 2016. CCF A. Cite 228. paper 🔥

  • (TransA) Yantao Jia, Yuanzhuo Wang, Hailun Lin, Xiaolong Jin, Xueqi Cheng. "Locally Adaptive Translation for Knowledge Graph Embedding". AAAI 2016. CCF A. Cite 80. paper 🔥

  • (TKRL) Ruobing Xie, Zhiyuan Liu, Maosong Sun. "Representation Learning of Knowledge Graphs with Hierarchical Types". IJCAI 2016. CCF A. Cite 140. paper code 🔥

  • (TEKE) Zhigang Wang, Juanzi Li. "Text-Enhanced Representation Learning for Knowledge Graph". IJCAI 2016. CCF A. Cite 113. paper 🔥

  • (ManifoldE) Han Xiao, Minlie Huang, Xiaoyan Zhu. "From One Point to a Manifold: Knowledge Graph Embedding for Precise Link Prediction". IJCAI 2016. CCF A. Cite 82. paper code 🔥

  • (KR-EAR) Yankai Lin, Zhiyuan Liu, Maosong Sun. "Knowledge Representation Learning with Entities, Attributes and Relations". IJCAI 2016. CCF A. Cite 49. paper code

  • (ProPPR) William Yang Wang, William W. Cohen. "Learning First-Order Logic Embeddings via Matrix Factorization". IJCAI 2016. CCF A. Cite 48. paper code

  • Jianfeng Wen, Jianxin Li, Yongyi Mao, Shini Chen, Richong Zhang. "On the Representation and Embedding of Knowledge Bases beyond Binary Relations". IJCAI 2016. CCF A. Cite 22. paper

  • (TransG) Han Xiao, Minlie Huang, Xiaoyan Zhu. "TransG: A Generative Model for Knowledge Graph Embedding". ACL 2016. CCF A. Cite 194. paper code 🔥

  • Teng Long, Ryan Lowe, Jackie Chi Kit Cheung, Doina Precup. "Leveraging Lexical Resources for Learning Entity Embeddings in Multi-Relational Data". ACL 2016. CCF A. Cite 18. paper

  • (HiRi) Qiao Liu, Liuyi Jiang, Minghao Han, Yao Liu, Zhiguang Qin. "Hierarchical Random Walk Inference in Knowledge Graphs". SIGIR 2016. CCF A. Cite 22. paper

  • (KALE) Shu Guo, Quan Wang, Lihong Wang, Bin Wang, Li Guo."Jointly Embedding Knowledge Graphs and Logical Rules". EMNLP 2016. CCF B. Cite 110. paper code 🔥

  • (t-TransE) Tingsong Jiang, Tianyu Liu, Tao Ge, Lei Sha, Sujian Li, Baobao Chang, Zhifang Sui. "Encoding Temporal Information for Time-Aware Link Prediction". EMNLP 2016. CCF B. Cite 35. paper

  • (FTransE) Jun Feng, Minlie Huang, Mingdong Wang, Mantong Zhou, Yu Hao, Xiaoyan Zhu. "Knowledge Graph Embedding by Flexible Translation". KR 2016. CCF B. Cite 58. paper code

  • (GAKE) Jun Feng, Minlie Huang, Yang Yang, Xiaoyan Zhu. "GAKE: Graph Aware Knowledge Embedding". COLING 2016. CCF B. Cite 58. paper code

  • (TransE-TAE) Tingsong Jiang, Tianyu Liu, Tao Ge, Lei Sha, Baobao Chang, Sujian Li, Zhifang Sui. "Towards Time-Aware Knowledge Graph Completion". COLING 2016. CCF B. Cite 38. paper

  • (STransE) Dat Quoc Nguyen, Kairit Sirts, Lizhen Qu, Mark Johnson. "STransE: A Novel Embedding Model of Entities and Relationships in Knowledge Bases". HLT-NAACL 2016. CCF C. Cite 129. paper code 🔥

  • (lppTransE) Hee-Geun Yoon, Hyun-Je Song, Seong-Bae Park, Se-Young Park. "A Translation-Based Knowledge Graph Embedding Preserving Logical Property of Relations". HLT-NAACL 2016. CCF C. Cite 44. paper

  • Changwei Hu, Piyush Rai, Lawrence Carin. "Topic-Based Embeddings for Learning from Large Knowledge Graphs". AISTATS 2016. CCF C. Cite 9. paper

  • Yinchong Yang, Cristóbal Esteban, Volker Tresp. "Embedding Mapping Approaches for Tensor Factorization and Knowledge Graph Modelling". ESWC 2016. CCF C. Cite 3. paper

2017

Journal

  • (LPMR) Caiyan Dai, Ling Chen, Bin Li, Yun Li. "Link prediction in multi-relational networks based on relational similarity". Information Sciences 2017. Sci 1. Impact 5.910. Cite 26. paper 🔥

  • Lidong Bing, Zhiming Zhang, Wai Lam, William W. Cohen. "Towards a language-independent solution: Knowledge base completion by searching the Web and deriving language pattern". Knowledge-based Systems 2017. Sci 2. Impact 5.921. Cite 4. paper

  • (SSE) Shu Guo, Quan Wang, Bin Wang, Lihong Wang, Li Guo. "SSE: Semantically Smooth Embedding for Knowledge Graphs". IEEE Transactions on Knowledge and Data Engineering 2017. Sci 2. Impact 4.935. Cite 22. paper 🔥

  • (TRANSFER) Xiaochi Wei, Heyan Huang, Liqiang Nie, Hanwang Zhang, Xianling Mao, Tat-Seng Chua. "I Know What You Want to Express: Sentence Element Inference by Incorporating External Knowledge Base". IEEE Transactions on Knowledge and Data Engineering 2017. Sci 2. Impact 4.935. Cite 9. paper code

  • (TransPES) Yu Wu, Tingting Mu, John Yannis Goulermas. "Translating on pairwise entity space for knowledge graph embedding". Neurocomputing 2017. Sci 2. Impact 4.438. Cite 6. paper code

  • Liang Chang, Manli Zhu, Tianlong Gu, Chenzhong Bin, Junyan Qian, Ji Zhang. "Knowledge Graph Embedding by Dynamic Translation". IEEE Access 2017. Sci 2. Impact 3.745. Cite 18. paper

  • (ComplEx) Théo Trouillon, Christopher R. Dance, Éric Gaussier, Johannes Welbl, Sebastian Riedel, Guillaume Bouchard. "Knowledge Graph Completion via Complex Tensor Factorization". Journal of Machine Learning Research 2017. Sci 2. Impact 3.484. Cite 107. paper code 🔥

  • Nico Potyka, Matthias Thimm. "Inconsistency-tolerant reasoning over linear probabilistic knowledge bases". International Journal of Approximate Reasoning 2017. Sci 3. Impact 2.678. Cite 4. paper

Conference

  • (Neural-LP) Fan Yang, Zhilin Yang, William W. Cohen. "Differentiable Learning of Logical Rules for Knowledge Base Reasoning". NIPS 2017. CCF A. Cite 150. paper reviews code 🔥

  • (ANALOGY) Hanxiao Liu, Yuexin Wu, Yiming Yang. "Analogical Inference for Multi-relational Embeddings". ICML 2017. CCF A. Cite 164. paper code 🔥

  • (Know-Evolve) Rakshit Trivedi, Hanjun Dai, Yichen Wang, Le Song. "Know-Evolve: Deep Temporal Reasoning for Dynamic Knowledge Graphs". ICML 2017. CCF A. Cite 124.paper 🔥

  • (ProjE) Baoxu Shi, Tim Weninger. "ProjE: Embedding Projection for Knowledge Graph Completion". AAAI 2017. CCF A. Cite 150. paper code 🔥

  • (SSP) Han Xiao, Minlie Huang, Lian Meng, Xiaoyan Zhu. "SSP: Semantic Space Projection for Knowledge Graph Embedding with Text Descriptions". AAAI 2017. CCF A. Cite 99. paper code 🔥

  • (MLNs) Melisachew Wudage Chekol, Giuseppe Pirrò, Joerg Schoenfisch, Heiner Stuckenschmidt. "Marrying Uncertainty and Time in Knowledge Graphs". AAAI 2017. CCF A. Cite 34. paper

  • (puTransE) Yi Tay, Luu Anh Tuan, Siu Cheung Hui. "Non-Parametric Estimation of Multiple Embeddings for Link Prediction on Dynamic Knowledge Graphs". AAAI 2017. CCF A. Cite 22. paper

  • (Jointly(A-LSTM)) Jiacheng Xu, Xipeng Qiu, Kan Chen, Xuanjing Huang. "Knowledge Graph Representation with Jointly Structural and Textual Encoding". IJCAI 2017. CCF A. Cite 57. paper code 🔥

  • (IKRL) Ruobing Xie, Zhiyuan Liu, Huanbo Luan, Maosong Sun. "Image-embodied Knowledge Representation Learning". IJCAI 2017. CCF A. Cite 46. paper code

  • (ITransF) Qizhe Xie, Xuezhe Ma, Zihang Dai, Eduard Hovy. "An Interpretable Knowledge Transfer Model for Knowledge Base Completion". ACL 2017. CCF A. Cite 45. paper

  • (FRN) Alexandros Komninos, Suresh Manandhar. "Feature-Rich Networks for Knowledge Base Completion". ACL 2017. CCF A. Cite 5. paper

  • Wen Zhang. "Knowledge Graph Embedding with Diversity of Structures". WWW 2017. CCF A. Cite 11. paper

  • Vibhor Kanojia, Hideyuki Maeda, Riku Togashi, Sumio Fujita. "Enhancing Knowledge Graph Embedding with Probabilistic Negative Sampling". WWW 2017. CCF A. Cite 5. paper

  • (DeepPath) Wenhan Xiong, Thien Hoang, William Yang Wang. "DeepPath: A Reinforcement Learning Method for Knowledge Graph Reasoning". EMNLP 2017. CCF B. Cite 180. paper 🔥

  • Jay Pujara, Eriq Augustine, Lise Getoor. "Sparsity and Noise: Where Knowledge Graph Embeddings Fall Short". EMNLP 2017. CCF B. Cite 41. paper code

  • (ETE) Changsung Moon, Paul Jones, Nagiza F. Samatova. "Learning Entity Type Embeddings for Knowledge Graph Completion". CIKM 2017. CCF B. Cite 22. paper

  • (TransE-RS) Xiaofei Zhou, Qiannan Zhu, Ping Liu, Li Guo. "Learning Knowledge Embeddings by Combining Limit-based Scoring Loss". CIKM 2017. CCF B. Cite 19. paper

  • (TCE) Jun Shi, Huan Gao, Guilin Qi, Zhangquan Zhou. "Knowledge Graph Embedding with Triple Context". CIKM 2017. CCF B. Cite 12. paper code

  • (CombinE) Zhen Tan, Xiang Zhao, Wei Wang. "Representation Learning of Large-Scale Knowledge Graphs via Entity Feature Combinations". CIKM 2017. CCF B. Cite 5. paper

  • Soumajit Pal, Jacopo Urbani. "Enhancing Knowledge Graph Completion By Embedding Correlations". CIKM 2017. CCF B. Cite 2. paper code

  • Pasquale Minervini, Luca Costabello, Emir Muñoz, Vít Novácek, Pierre-Yves Vandenbussche. "Regularizing Knowledge Graph Embeddings via Equivalence and Inversion Axioms". ECML/PKDD 2017. CCF B. Cite 31. paper

  • Shiheng Ma, Jianhui Ding, Weijia Jia, Kun Wang, Minyi Guo. "TransT: Type-Based Multiple Embedding Representations for Knowledge Graph Completion". ECML/PKDD 2017. CCF B. Cite 24. paper

  • Zhijuan Du, Zehui Hao, Xiaofeng Meng, Qiuyue Wang. "CirE: Circular Embeddings of Knowledge Graphs". DASFAA 2017. CCF B. Cite 3. paper

  • (RSTE) Yi Tay, Anh Tuan Luu, Siu Cheung Hui, Falk Brauer. "Random Semantic Tensor Ensemble for Scalable Knowledge Graph Link Prediction". WSDM 2017. CCF B. Cite 13. paper

2018

Journal

  • (PaSKoGE) Yantao Jia, Yuanzhuo Wang, Xiaolong Jin, Xueqi Cheng. "Path-specific knowledge graph embedding". Knowledge-based Systems 2018. Sci 2. Impact 5.921. Cite 10. paper

  • Lirong He, Bin Liu, Guangxi Li, Yongpan Sheng, Yafang Wang, Zenglin Xu. "Knowledge Base Completion by Variational Bayesian Neural Tensor Decomposition". Cognitive Computation 2018. Sci 2. Impact 4.287. Cite 16. paper 🔥

  • Zhen Tan, Xiang Zhao, Yang Fang, Weidong Xiao. "GTrans: Generic Knowledge Graph Embedding via Multi-State Entities and Dynamic Relation Spaces". IEEE Access 2018. Sci 2. Impact 3.745. Cite 12. paper

  • Huan Gao, Jun Shi, Guilin Qi, Meng Wang. "Triple Context-Based Knowledge Graph Embedding". IEEE Access 2018. Sci 2. Impact 3.745. Cite 8. paper

  • Hyun-Je Song, Seong-Bae Park. "Enriching Translation-Based Knowledge Graph Embeddings Through Continual Learning". IEEE Access 2018. Sci 2. Impact 3.745. Cite 2. paper

  • Xiao Han, Chunhong Zhang, Tingting Sun, Yang Ji, Zheng Hu. "A Triple-Branch Neural Network for Knowledge Graph Embedding". IEEE Access 2018. Sci 2. Impact 3.745. Cite 1. paper

  • Jizhao Zhu, Yantao Jia, Jun Xu, Jianzhong Qiao, Xueqi Cheng. "Modeling the Correlations of Relations for Knowledge Graph Embedding. Journal of Computer Science and Technology 2018. Sci 3. Impact 1.506. Cite 8. paper

  • Yantao Jia, Yuanzhuo Wang, Xiaolong Jin, Hailun Lin, Xueqi Cheng. "Knowledge Graph Embedding: A Locally and Temporally Adaptive Translation-Based Approach". ACM Transactions on the Web 2018. Sci 4. Impact 1.157. Cite 10. paper

Conference

  • (MINERVA) Rajarshi Das, Shehzaad Dhuliawala, Manzil Zaheer, Luke Vilnis, Ishan Durugkar, Akshay Krishnamurthy, Alex Smola, Andrew McCallum. "Go for a Walk and Arrive at the Answer: Reasoning Over Paths in Knowledge Bases using Reinforcement Learning". ICLR 2018. CCF A. Cite 164. paper code 🔥

  • (SimplE) Seyed Mehran Kazemi, David Poole. "SimplE Embedding for Link Prediction in Knowledge Graphs". NeurIPS 2018. CCF A. Cite 163. paper reviews code 🔥

  • (GQE) William L. Hamilton, Payal Bajaj, Marinka Zitnik, Dan Jurafsky, Jure Leskovec. "Embedding Logical Queries on Knowledge Graphs". NeurIPS 2018. CCF A. Cite 66. paper reviews code 🔥

  • (ComplEx-N3) Timothée Lacroix, Nicolas Usunier, Guillaume Obozinski. "Canonical Tensor Decomposition for Knowledge Base Completion". ICML 2018. CCF A. Cite 113. paper code 🔥

  • (ConvE) Tim Dettmers, Pasquale Minervini, Pontus Stenetorp, Sebastian Riedel. "Convolutional 2D Knowledge Graph Embeddings". AAAI 2018. CCF A. Cite 512. paper code 🔥

  • (TorusE) Takuma Ebisu, Ryutaro Ichise. "TorusE: Knowledge Graph Embedding on a Lie Group". AAAI 2018. CCF A. Cite 78. paper code 🔥

  • (RUGE) Shu Guo, Quan Wang, Lihong Wang, Bin Wang, Li Guo. "Knowledge Graph Embedding With Iterative Guidance From Soft Rules". AAAI 2018. CCF A. Cite 74. paper code 🔥

  • (ConMask) Baoxu Shi, Tim Weninger. "Open-World Knowledge Graph Completion". AAAI 2018. CCF A. Cite 73. paper code "fire"

  • (JointNRE) Xu Han, Zhiyuan Liu, Maosong Sun. "Neural Knowledge Acquisition via Mutual Attention Between Knowledge Graph and Text". AAAI 2018. CCF A. Cite 55. paper code 🔥

  • (IGAN) Peifeng Wang, Shuangyin Li, Rong Pan. "Incorporating GAN for Negative Sampling in Knowledge Representation Learning". AAAI 2018. CCF A. Cite 39. paper

  • Yanjie Wang, Rainer Gemulla, Hui Li. "On Multi-Relational Link Prediction with Bilinear Models". AAAI 2018. CCF A. Cite 28. paper code

  • (CKRL) Ruobing Xie, Zhiyuan Liu, Fen Lin, Leyu Lin. "Does William Shakespeare REALLY Write Hamlet? Knowledge Representation Learning With Confidence". AAAI 2018. CCF A. Cite 19. paper code

  • (ComplEx-L1) Hitoshi Manabe, Katsuhiko Hayashi, Masashi Shimbo. "Data-Dependent Learning of Symmetric/Antisymmetric Relations for Knowledge Base Completion". AAAI 2018. CCF A. Cite 7. paper code

  • (TransE-T) Richong Zhang, Fanshuang Kong, Chenyue Wang, Yongyi Mao. "Embedding of Hierarchically Typed Knowledge Bases". AAAI 2018. CCF A. Cite 2. paper code

  • (TransAt) Wei Qian, Cong Fu, Yu Zhu, Deng Cai, Xiaofei He. "Translating Embeddings for Knowledge Graph Completion with Relation Attention Mechanism". IJCAI 2018. CCF A. Cite 19. paper code

  • (ComplEx-NNE) Boyang Ding, Quan Wang, Bin Wang, Li Guo. "Improving Knowledge Graph Embedding Using Simple Constraints". ACL 2018. CCF A. Cite 48. paper code 🔥

  • Luke Vilnis, Xiang Li, Shikhar Murty, Andrew McCallum. "Probabilistic Embedding of Knowledge Graphs with Box Lattice Measures". ACL 2018. CCF A. Cite 40. paper

  • (KG-Geometry) Chandrahas, Aditya Sharma, Partha Talukdar. "Towards Understanding the Geometry of Knowledge Graph Embeddings". ACL 2018. CCF A. Cite 22. paper code

  • Ryo Takahashi, Ran Tian, Kentaro Inui. "Interpretable and Compositional Relation Learning by Joint Training with an Autoencoder". ACL 2018. CCF A. Cite 4. paper code

  • (TransN) Chun-Chih Wang, Pu-Jen Cheng. "Translating Representations of Knowledge Graphs with Neighbors". SIGIR 2018. CCF A. Cite 3. paper

  • (Max-K Criterion) Jiajie Mei, Richong Zhang, Yongyi Mao, Ting Deng. "On Link Prediction in Knowledge Bases: Max-K Criterion and Prediction Protocols". SIGIR 2018. CCF A. Cite 1. paper

  • (TTransE) Julien Leblay, Melisachew Wudage Chekol. "Deriving Validity Time in Knowledge Graph". WWW 2018. CCF A. Cite 34. paper

  • Kaja Zupanc, Jesse Davis. "Estimating Rule Quality for Knowledge Base Completion with the Relationship between Coverage Assumption". WWW 2018. CCF A. Cite 18. paper

  • (KBLRN) Alberto García-Durán, Mathias Niepert. "KBlrn: End-to-End Learning of Knowledge Base Representations with Latent, Relational, and Numerical Features". UAI 2018. CCF B. Cite 41. paper 🔥

  • (MultiHopKG) Xi Victoria Lin, Richard Socher, Caiming Xiong. "Multi-Hop Knowledge Graph Reasoning with Reward Shaping". EMNLP 2018. CCF B. Cite 69. paper code 🔥

  • (HyTE) Shib Sankar Dasgupta, Swayambhu Nath Ray, Partha Talukdar. "HyTE: Hyperplane-based Temporally aware Knowledge Graph Embedding". EMNLP 2018. CCF B. Cite 50. paper code 🔥

  • (GMatching) Wenhan Xiong, Mo Yu, Shiyu Chang, Xiaoxiao Guo, William Yang Wang. "One-Shot Relational Learning for Knowledge Graphs". EMNLP 2018. CCF B. Cite 40. paper code

  • (TA-DistMult) Alberto Garcia-Duran, Sebastijan Dumančić, Mathias Niepert. "Learning Sequence Encoders for Temporal Knowledge Graph Completion". EMNLP 2018. CCF B. Cite 39. paper dataset

  • (TransC) Xin Lv, Lei Hou, Juanzi Li, Zhiyuan Liu. "Differentiating Concepts and Instances for Knowledge Graph Embedding". EMNLP 2018. CCF B. Cite 30. paper code

  • (MKBE) Pouya Pezeshkpour, Liyan Chen, Sameer Singh. "Embedding Multimodal Relational Data for Knowledge Base Completion". EMNLP 2018. CCF B. Cite 28. paper code

  • (TransE-HRS) Zhao Zhang, Fuzhen Zhuang, Meng Qu, Fen Lin, Qing He. "Knowledge Graph Embedding with Hierarchical Relation Structure". EMNLP 2018. CCF B. Cite 17. paper

  • Víctor Gutiérrez-Basulto, Steven Schockaert. "From Knowledge Graph Embedding to Ontology Embedding? An Analysis of the Compatibility between Vector Space Representations and Rules". KR 2018. CCF B. Cite 24. paper

  • Farahnaz Akrami, Lingbing Guo, Wei Hu, Chengkai Li. "Re-evaluating Embedding-Based Knowledge Graph Completion Methods". CIKM 2018. CCF B. Cite 12. paper

  • (SENN) Saiping Guan, Xiaolong Jin, Yuanzhuo Wang, Xueqi Cheng. "Shared Embedding Based Neural Networks for Knowledge Graph Completion". CIKM 2018. CCF B. Cite 12. paper

  • (CACL) Byungkook Oh, Seungmin Seo, Kyong-Ho. "Knowledge Graph Completion by Context-Aware Convolutional Learning with Multi-Hop Neighborhoods". CIKM 2018. CCF B. Cite 10. paper

  • (MultiE) Zhao Zhang, Fuzhen Zhuang, Zheng-Yu Niu, Deqing Wang, Qing He. "MultiE: Multi-Task Embedding for Knowledge Base Completion". CIKM 2018. CCF B. Cite 2. paper

  • Benjamin J. Lengerich, Andrew L. Maas, Christopher Potts. "Retrofitting Distributional Embeddings to Knowledge Graphs with Functional Relations". COLING 2018. CCF B. Cite 19. paper

  • (R-GCN) Michael Schlichtkrull, Thomas N. Kipf, Peter Bloem, Rianne van den Berg, Ivan Titov, Max Welling. "Modeling Relational Data with Graph Convolutional Networks". ESWC 2018. CCF C. Cite 855. paper code 🔥

  • Itsumi Saito, Kyosuke Nishida, Hisako Asano, Junji Tomita. "Commonsense Knowledge Base Completion and Generation". CoNLL 2018. CCF C. Cite 17. paper

  • (ConvKB) Dai Quoc Nguyen, Tu Dinh Nguyen, Dat Quoc Nguyen, Dinh Phung. "A Novel Embedding Model for Knowledge Base Completion Based on Convolutional Neural Network". NAACL-HLT 2018. CCF C. Cite 168. paper code 🔥

  • (KBGAN) Liwei Cai, William Yang Wang. "KBGAN: Adversarial Learning for Knowledge Graph Embeddings". NAACL-HLT 2018. CCF C. Cite 116. paper code 🔥

  • (ATE) Bo An, Bo Chen, Xianpei Han, Le Sun. "Accurate Text-Enhanced Knowledge Graph Representation Learning". NAACL-HLT 2018. CCF C. Cite 26. paper

2019

Journal

  • (TKGE) Binling Nie, Shouqian Sun. "Knowledge graph embedding via reasoning over entities, relations, and text". Future Generation Computer Systems 2019. Sci 1. Impact 6.125. Cite 12. paper 🔥

  • (KEC) Niannian Guan, Dandan Song, Lejian Liao. "Knowledge graph embedding with concepts". Knowledge-based Systems 2019. Sci 2. Impact 5.921. Cite 24. paper 🔥 💥

  • (ProjFE) Huajing Liu, Luyi Bai, Xiangnan Ma, Wenting Yu, Changming Xu. "ProjFE: Prediction of fuzzy entity and relation for knowledge graph completion". Applied Soft Computing 2019. Sci 2. Impact 5.472. Cite 4. paper

  • Xing Tang, Ling Chen, Jun Cui, Baogang Wei. "Knowledge representation learning with entity descriptions, hierarchical types, and textual relations". Information Processing and Management 2019. Sci 2. Impact 4.787. Cite 8. paper

  • (RPE) Xixun Lin, Yanchun Liang, Fausto Giunchiglia, Xiaoyue Feng, Renchu Guan. "Relation path embedding in knowledge graphs". Neural Computing and Applications 2019. Sci 2. Impact 4.774. Cite 10. paper

  • Ming He, Xiangkun Du, Bo Wang. "Representation Learning of Knowledge Graphs via Fine-Grained Relation Description Combinations". IEEE Access 2019. Sci 2. Impact 3.745. Cite 3. paper

  • Xiaojun Kang, Hong Yao, Qingtao Li, Xinchuan Li, Chao Liu, Lijun Dong. "TDN: An Integrated Representation Learning Model of Knowledge Graphs". IEEE Access 2019. Sci 2. Impact 3.745. Cite 2. paper

  • Jingpei Lei, Dantong Ouyang, Ying Liu. "Adversarial Knowledge Representation Learning Without External Model". IEEE Access 2019. Sci 2. Impact 3.745. Cite 1. paper

  • Wen'an Zhou, Shirui Wang, Chao Jiang. "Knowledge Graph Embedding With Interactive Guidance From Entity Descriptions". IEEE Access 2019. Sci 2. Impact 3.745. Cite 1. paper

  • Weidong Li, Xinyu Zhang, Yaqian Wang, Zhihuan Yan, Rong Peng. "Graph2Seq: Fusion Embedding Learning for Knowledge Graph Completion". IEEE Access 2019. Sci 2. Impact 3.745. Cite 1. paper

  • Chengchun Shi, Wenbin Lu, Rui Song. "Determining the Number of Latent Factors in Statistical Multi-Relational Learning". Journal of Machine Learning Research 2019. Sci 2. Impact 3.484. Cite 3. paper

  • (ConvKB) Dai Quoc Nguyen, Dat Quoc Nguyen, Tu Dinh Nguyen, Dinh Phung. "A convolutional neural network-based model for knowledge base completion and its application to search personalization". Semantic Web 2019. Sci 3. Impact 3.182. Cite 7. paper

  • Qiannan Zhu, Xiaofei Zhou, Peng Zhang, Yong Shi. "A neural translating general hyperplane for knowledge graph embedding". Journal of Computational Science 2019. Sci 3. Impact 2.644. Cite 6. paper

  • Yu Zhao, Huali Feng, Patrick Gallinari. "Embedding Learning with Triple Trustiness on Noisy Knowledge Graph". Entropy 2019. Sci 3. Impact 2.494. Cite 2. paper

  • (ConT) Yunpu Ma, Volker Tresp, Erik A. Daxberger. "Embedding models for episodic knowledge graphs". Journal of Web Semantics 2019. Sci 4. Impact 2.238. Cite 18. paper 🔥

  • Ankur Padia, Konstantinos Kalpakis, Francis Ferraro, Tim Finin. "Knowledge Graph Fact Prediction via Knowledge-Enriched Tensor Factorization". Journal of Web Semantics 2019. Sci 4. Impact 2.238. Cite 9. paper code

  • (AWML) Chenchen Guo, Chunhong Zhang, Xiao Han, Yang Ji. "AWML: adaptive weighted margin learning for knowledge graph embedding". Journal of Intelligent Information Systems 2019. Sci 4. Impact 1.813. Cite 0. paper

Conference

  • (RotatE) Zhiqing Sun, Zhi-Hong Deng, Jian-Yun Nie, Jian Tang. "RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space". ICLR 2019. CCF A. Cite 231. paper code 🔥 💥

  • (DyRep) Rakshit Trivedi, Mehrdad Farajtabar, Prasenjeet Biswal, Hongyuan Zha. "DyRep: Learning Representations over Dynamic Graphs". ICLR 2019. CCF A. Cite 56. paper 🔥 💥

  • (QuatE) Shuai Zhangy, Yi Tay, Lina Yao, Qi Liu. "Quaternion Knowledge Graph Embeddings". NeurIPS 2019. CCF A. Cite 62. paper code 🔥

  • (MuRP) Ivana Balaževic, Carl Allen, Timothy Hospedales. "Multi-relational Poincaré Graph Embeddings". NeurIPS 2019. CCF A. Cite 28. paper code 🔥

  • (DRUM) Ali Sadeghian, Mohammadreza Armandpour, Patrick Ding, Daisy Zhe Wang. "DRUM: End-To-End Differentiable Rule Mining On Knowledge Graphs". NeurIPS 2019. CCF A. Cite 13. paper code

  • (RSN) Lingbing Guo, Zequn Sun, Wei Hu. "Learning to Exploit Long-term Relational Dependencies in Knowledge Graphs". ICML 2019. CCF A. Cite 41. paper code 🔥

  • (SACN) Chao Shang, Yun Tang, Jing Huang, Jinbo Bi, Xiaodong He, Bowen Zhou. "End-to-End Structure-Aware Convolutional Networks for Knowledge Base Completion". AAAI 2019. CCF A. Cite 55. paper code 🔥

  • (UKGE) Xuelu Chen, Muhao Chen, Weijia Shi, Yizhou Sun, Carlo Zaniolo. "Embedding Uncertain Knowledge Graphs". AAAI 2019. CCF A. Cite 19. paper code

  • (SimplE+) Bahare Fatemi, Siamak Ravanbakhsh, David Poole. "Improved Knowledge Graph Embedding Using Background Taxonomic Information". AAAI 2019. CCF A. Cite 15. paper

  • (LAN) PeiFeng Wang, Jialong Han, Chenliang Li, Rong Pan. "Logic Attention Based Neighborhood Aggregation for Inductive Knowledge Graph Embedding". AAAI 2019. CCF A. Cite 13. paper code

  • (OWE) Haseeb Shah, Johannes Villmow, Adrian Ulges, Ulrich Schwanecke, Faisal Shafait. "An Open-World Extension to Knowledge Graph Completion Models". AAAI 2019. CCF A. Cite 10. paper code

  • (TransGate) Jun Yuan, Neng Gao, Ji Xiang. "TransGate: Knowledge Graph Embedding with Shared Gate Structure". AAAI 2019. CCF A. Cite 8. paper

  • (LENA) Fanshuang Kong, Richong Zhang, Yongyi Mao, Ting Deng. "LENA: Locality-Expanded Neural Embedding for Knowledge Base Completion". AAAI 2019. CCF A. Cite 2. paper code

  • (AnyBURL) Christian Meilicke, Melisachew Wudage Chekol, Daniel Ruffinelli, Heiner Stuckenschmidt. "Anytime Bottom-Up Rule Learning for Knowledge Graph Completion". IJCAI 2019. CCF A. Cite 24. paper code

  • (VR-GCN) Rui Ye, Xin Li, Yujie Fang, Hongyu Zang, Mingzhong Wang. "A Vectorized Relational Graph Convolutional Network for Multi-Relational Network Alignment". IJCAI 2019. CCF A. Cite 21. paper

  • (TransMS) Shihui Yang, Jidong Tian, Honglun Zhang, Junchi Yan, Hao He, Yaohui Jin. "TransMS: Knowledge Graph Embedding for Complex Relations by Multidirectional Semantics". IJCAI 2019. CCF A. Cite 12. paper

  • Hengtong Zhang, Tianhang Zheng, Jing Gao, Chenglin Miao, Lu Su, Yaliang Li, Kui Ren. "Data Poisoning Attack against Knowledge Graph Embedding". IJCAI 2019. CCF A. Cite 6. paper

  • (M-GNN) Zihan Wang, Zhaochun Ren, Chunyu He, Peng Zhang, Yue Hu. "Robust Embedding with Multi-Level Structures for Link Prediction". IJCAI 2019. CCF A. Cite 5. paper

  • (WWV) Neil Veira, Brian Keng, Kanchana Padmanabhan, Andreas G. Veneris. "Unsupervised Embedding Enhancements of Knowledge Graphs using Textual Associations". IJCAI 2019. CCF A. Cite 3. paper code

  • (KBGAT) Deepak Nathani, Jatin Chauhan, Charu Sharma, Manohar Kaul. "Learning Attention-based Embeddings for Relation Prediction in Knowledge Graphs". ACL 2019. CCF A. Cite 67. paper code 🔥 💥

  • (DihEdral) Canran Xu, Ruijiang Li. "Relation Embedding with Dihedral Group in Knowledge Graph". ACL 2019. CCF A. Cite 19. paper

  • (JOIE) Junheng Hao, Muhao Chen, Wenchao Yu, Yizhou Sun, Wei Wang. "Universal Representation Learning of Knowledge Bases by Jointly Embedding Instances and Ontological Concepts". KDD 2019. CCF A. Cite 25. paper code

  • (NSCaching) Yongqi Zhang, Quanming Yao, Yingxia Shao, Lei Chen. "NSCaching: Simple and Efficient Negative Sampling for Knowledge Graph Embedding". ICDE 2019. CCF A. Cite 22. paper code

  • (IterE) Wen Zhang, Bibek Paudel, Liang Wang, Jiaoyan Chen, Hai Zhu, Wei Zhang, Abraham Bernstein, Huajun Chen. "Iteratively Learning Embeddings and Rules for Knowledge Graph Reasoning". WWW 2019. CCF A. Cite 30. paper code 🔥

  • (NaLP) Saiping Guan, Xiaolong Jin, Yuanzhuo Wang, Xueqi Cheng. "Link Prediction on N-ary Relational Data". WWW 2019. CCF A. Cite 10. paper code

  • (ActiveLink) Natalia Ostapuk, Jie Yang, Philippe Cudré-Mauroux. "ActiveLink: Deep Active Learning for Link Prediction in Knowledge Graphs". WWW 2019. CCF A. Cite 9. paper code

  • (MARINE) Ming-Han Feng, Chin-Chi Hsu, Cheng-Te Li, Mi-Yen Yeh, Shou-De Lin. "MARINE: Multi-relational Network Embeddings with Relational Proximity and Node Attributes". WWW 2019. CCF A. Cite 7. paper

  • (TuckER) Ivana Balazevic, Carl Allen, Timothy M. Hospedales. "TuckER: Tensor Factorization for Knowledge Graph Completion". EMNLP/IJCNLP 2019. CCF B. Cite 92. paper code 🔥 💥

  • (MetaR) Mingyang Chen, Wen Zhang, Wei Zhang, Qiang Chen and Huajun Chen. "Meta Relational Learning for Few-Shot Link Prediction in Knowledge Graphs". EMNLP/IJCNLP 2019. CCF B. Cite 18. paper code

  • (Meta-KGR) Xin Lv, Yuxian Gu, Xu Han, Lei Hou, Juanzi Li, Zhiyuan Liu. "Adapting Meta Knowledge Graph Information for Multi-Hop Reasoning over Few-Shot Relations". EMNLP/IJCNLP 2019. CCF B. Cite 9. paper

  • (CPL) Cong Fu, Tong Chen, Meng Qu, Woojeong Jin, Xiang Ren. "Collaborative Policy Learning for Open Knowledge Graph Reasoning". EMNLP/IJCNLP 2019. CCF B. Cite 7. paper

  • (CaRe) Swapnil Gupta, Sreyash Kenkre, Partha Talukdar. "CaRe: Open Knowledge Graph Embeddings". EMNLP/IJCNLP 2019. CCF B. Cite 3. paper code

  • Heng Wang, Shuangyin Li, Rong Pan, Mingzhi Mao. "Incorporating Graph Attention Mechanism into Knowledge Graph Reasoning Based on Deep Reinforcement Learning". EMNLP/IJCNLP 2019. CCF B. Cite 3. paper

  • (TCVAE) Zihao Wang, Kwunping Lai, Piji Li, Lidong Bing and Wai Lam. "Tackling Long-Tailed Relations and Uncommon Entities in Knowledge Graph Completion". EMNLP/IJCNLP 2019. CCF B. Cite 2. paper

  • (OPTransE) Yao Zhu, Hongzhi Liu, Zhonghai Wu, Yang Song and Tao Zhang. "Representation Learning with Ordered Relation Paths for Knowledge Graph Completion". EMNLP/IJCNLP 2019. CCF B. Cite 2. paper

  • (JoBi ComplEx) Esma Balkir, Masha Naslidnyk, Dave Palfrey and Arpit Mittal. "Using Pairwise Occurrence Information to Improve Knowledge Graph Completion on Large-Scale Datasets". EMNLP/IJCNLP 2019. CCF B. Cite 0. paper

  • Ondrej Kuzelka, Jesse Davis. "Markov Logic Networks for Knowledge Base Completion: A Theoretical Analysis Under the MCAR Assumption". UAI 2019. CCF B. Cite 4. paper

  • (EM) Robert Bamler, Farnood Salehi, Stephan Mandt. "Augmenting and Tuning Knowledge Graph Embeddings". UAI 2019. CCF B. Cite 2. paper code

  • Agustinus Kristiadi, Mohammad Asif Khan, Denis Lukovnikov, Jens Lehmann, Asja Fischer. "Incorporating Literals into Knowledge Graph Embeddings. ISWC 2019. CCF B. Cite 17. paper

  • Zequn Sun, JiaCheng Huang, Wei Hu, Muhao Chen, Lingbing Guo, Yuzhong Qu. "TransEdge: Translating Relation-Contextualized Embeddings for Knowledge Graphs". ISWC 2019. CCF B. Cite 11. paper

  • Erik B. Myklebust, Ernesto Jiménez-Ruiz, Jiaoyan Chen, Raoul Wolf, Knut Erik Tollefsen. "Knowledge Graph Embedding for Ecotoxicological Effect Prediction". ISWC 2019. CCF B. Cite 8. paper

  • Mehdi Ali, Hajira Jabeen, Charles Tapley Hoyt, Jens Lehmann. "The KEEN Universe - An Ecosystem for Knowledge Graph Embeddings with a Focus on Reproducibility and Transferability". ISWC 2019. CCF B. Cite 6. paper

  • Changjian Wang, Minghui Yan, Chuanrun Yi, Ying Sha. "Capturing Semantic and Syntactic Information for Link Prediction in Knowledge Graphs". ISWC 2019. CCF B. Cite 1. paper

  • Simon Gottschalk, Elena Demidova. "HapPenIng: Happen, Predict, Infer - Event Series Completion in a Knowledge Graph". ISWC 2019. CCF B. Cite 0. paper

  • Vassilis N. Ioannidis, Antonio G. Marques, Georgios B. Giannakis. "A Recurrent Graph Neural Network for Multi-relational Data". ICASSP 2019. CCF B. Cite 11. paper

  • (CapsE) Dai Quoc Nguyen, Thanh Vu, Tu Dinh Nguyen, Dat Quoc Nguyen, Dinh Q. Phung. "A Capsule Network-based Embedding Model for Knowledge Graph Completion and Search Personalization". NAACL-HLT 2019. CCF C. Cite 43. paper code 🔥

  • Xiaotian Jiang, Quan Wang, Bin Wang. "Adaptive Convolution for Multi-Relational Learning". NAACL-HLT 2019. CCF C. Cite 15. paper

  • (ConvR) Xiaotian Jiang, Quan Wang, Bin Wang. "Adaptive Convolution for Multi-Relational Learning". NAACL-HLT 2019. CCF C. Cite 15. paper

  • (GRank) Takuma Ebisu, Ryutaro Ichise. "Graph Pattern Entity Ranking Model for Knowledge Graph Completion". NAACL-HLT 2019. CCF C. Cite 7. paper

  • (CRIAGE) Pouya Pezeshkpour, Yifan Tian, Sameer Singh. “Investigating Robustness and Interpretability of Link Prediction via Adversarial Modifications”. NAACL-HLT 2019. CCF C. Cite 7. paper code

  • Dingcheng Li, Siamak Zamani, Jingyuan Zhang, Ping Li. "Integration of Knowledge Graph Embedding Into Topic Modeling with Hierarchical Dirichlet Process". NAACL-HLT 2019. CCF C. Cite 4. paper

  • (FFD) Zihao Fu, Yankai Lin, Zhiyuan Liu, Wai Lam. "Fact Discovery from Knowledge Base via Facet Decomposition". NAACL-HLT 2019. CCF C. Cite 0. paper

  • Ye Liu, Hui Li, Alberto García-Durán, Mathias Niepert, Daniel O?oro-Rubio, David S. Rosenblum. "MMKG: Multi-modal Knowledge Graphs". ESWC 2019. CCF C. Cite 11. paper

  • Sébastien Ferré. "Link Prediction in Knowledge Graphs with Concepts of Nearest Neighbours". ESWC 2019. CCF C. Cite 2. paper

  • (CrossE) Wen Zhang, Bibek Paudel, Wei Zhang, Abraham Bernstein, Huajun Chen. "Interaction Embeddings for Prediction and Explanation in Knowledge Graphs". WSDM 2019. CCF C. Cite 37. paper code 🔥

2020

Journal

  • Yongming Han, GuoFei Chen, Zhongkun Li, Zhiqiang Geng, Fang Li, Bo Ma. "An asymmetric knowledge representation learning in manifold space". Information Sciences 2020. Sci 1. Impact 5.910. Cite 1. paper

  • Yuanfei Dai, Shiping Wang, Xing Chen, Chaoyang Xu, Wenzhong Guo. "Generative adversarial networks based on Wasserstein distance for knowledge graph embeddings". Knowledge Based Systems 2020. Sci 2. Impact 5.921. Cite 3. paper

  • Chen Li, Xutan Peng, Shanghang Zhang, Hao Peng, Philip S. Yu, Min He, Linfeng Du, Lihong Wang. "Modeling relation paths for knowledge base completion via joint adversarial training". Knowledge Based Systems 2020. Sci 2. Impact 5.921. Cite 0. paper

  • Qi Wang, Yongsheng Hao, Jie Cao. "ADRL: An attention-based deep reinforcement learning framework for knowledge graph reasoning". Knowledge Based Systems 2020. Sci 2. Impact 5.921. Cite 1. paper

  • Batselem Jagvaral, Wan-Kon Lee, Jae-Seung Roh, Min-Sung Kim, Young-Tack Park. "Path-based reasoning approach for knowledge graph completion using CNN-BiLSTM with attention mechanism". Expert Systems with Applications 2020. Sci 2. Impact 5.452. Cite 3. paper

  • Kai Lei, Jin Zhang, Yuexiang Xie, Desi Wen, Daoyuan Chen, Min Yang, Ying Shen. "Path-based reasoning with constrained type attention for knowledge graph completion". Neural Computing and Applications 2020. Sci 2. Impact 4.774. Cite 4. paper

  • Rui Wang , Bicheng Li , Shengwei Hu , Wenqian Du , Min Zhang. "Knowledge Graph Embedding via Graph Attenuated Attention Networks". IEEE Access 2020. Sci 2. Impact 3.745. Cite 6. paper

  • Yashen Wang , Huanhuan Zhang, Ge Shi , Zhirun Liu, Qiang Zhou. "A Model of Text-Enhanced Knowledge Graph Representation Learning With Mutual Attention". IEEE Access 2020. Sci 2. Impact 3.745. Cite 1. paper

  • (TDG2E) Xiaoli Tang, Rui Yuan, Qianyu Li, Tengyun Wang, Haizhi Yang, Yundong Cai, Hengjie Song. "Timespan-Aware Dynamic Knowledge Graph Embedding by Incorporating Temporal Evolution". IEEE Access 2020. Sci 2. Impact 3.745. Cite 1. paper

  • Seungmin Seo, Byungkook Oh, Kyong-Ho Lee. "Reliable Knowledge Graph Path Representation Learning". IEEE Access 2020. Sci 2. Impact 3.745. Cite 0. paper

  • Zhongwei Zhang, Lei Cao, Xiliang Chen, Wei Tang, Zhixiong Xu, Yangyang Meng. "Representation Learning of Knowledge Graphs With Entity Attributes". IEEE Access 2020. Sci 2. Impact 3.745. Cite 3. paper

  • Takuma Ebisu , Ryutaro Ichise. "Generalized Translation-Based Embedding of Knowledge Graph". IEEE Transactions on Knowledge and Data Engineering 2020. Sci 3. Impact 4.935. Cite 5. paper

  • Qi Wang , Yongsheng Hao. "ALSTM: An attention-based long short-term memory framework for knowledge base reasoning". Neurocomputing 2020. Sci 3. Impact 4.438. Cite 3. paper

  • Feng Zhao, Haoran Sun, Langjunqing Jin, Hai Jin. "Structure-augmented knowledge graph embedding for sparse data with rule learning". Computer Communications 2020. Sci 3. Impact 2.816. Cite 1. paper

  • Ruobing Xie, Stefan Heinrich, Zhiyuan Liu, Cornelius Weber, Yuan Yao, Stefan Wermter, Maosong Sun. "Integrating Image-Based and Knowledge-Based Representation Learning". IEEE Transactions on Cognitive and Developmental Systems 2020. Sci 3. Impact 2.667. Cite 0. paper

  • Jia Zhu, Zetao Zheng, Min Yang, Gabriel Pui Cheong Fung, Yong Tang. "A semi-supervised model for knowledge graph embedding". Data Mining and Knowledge Discovery 2020. Sci 3. Impact 2.629. Cite 0. paper

  • Fangfang Liu, Yan Shen, Tienan Zhang, Honghao Gao. "Entity-related paths modeling for knowledge base completion". Frontiers of Computer Science 2020. Sci 3. Impact 1.275. Cite 0. paper

  • Fengyuan Lu, Peijin Cong, Xinli Huang. Utilizing Textual Information in Knowledge Graph Embedding: A Survey of Methods and Applications. IEEE Access. paper

  • Jingbin Wang, Wang Zhang, Xinyuan Chen, Jing Lei, Xiaolian Lai. 3DRTE: 3D Rotation Embedding in Temporal Knowledge Graph. IEEE Access. paper

  • Yuhang Zhang, Jun Wang, Jie Luo. Knowledge Graph Embedding Based Collaborative Filtering. IEEE Access. paper

  • Kai Wang, Yu Liu, Xiujuan Xu, Quan Z. Sheng. Enhancing knowledge graph embedding by composite neighbors for link prediction. Computing. paper

  • Md. Mostafizur Rahman, Atsuhiro Takasu. "Leveraging Entity-Type Properties in the Relational Context for Knowledge Graph Embedding". IEICE Trans. Inf. Syst. 2020. paper

  • Siheng Zhang, Zhengya Sun, Wensheng Zhang. "Improve the translational distance models for knowledge graph embedding". J. Intell. Inf. Syst. 2020. paper

  • Knowledge graph entity typing via learning connecting embeddings

  • Aggregating neighborhood information for negative sampling for knowledge graph embedding

  • Multiview Translation Learning for Knowledge Graph Embedding

  • Representation Learning of Knowledge Graphs with Embedding Subspaces

  • Generalized Translation-Based Embedding of Knowledge Graph

  • Benchmarking neural embeddings for link prediction in knowledge graphs under semantic and structural changes

  • A Quaternion-Embedded Capsule Network Model for Knowledge Graph Completion

  • Hamming Distance Encoding Multihop Relation Knowledge Graph Completion

  • Knowledge Graph Completion: A Review

  • Graph Attention Networks With Local Structure Awareness for Knowledge Graph Completion

  • Knowledge graphs completion via probabilistic reasoning

  • Path-based reasoning approach for knowledge graph completion using CNN-BiLSTM with attention mechanism

  • GRL: Knowledge graph completion with GAN-based reinforcement learning

  • Path-based reasoning with constrained type attention for knowledge graph completion

  • Schema aware iterative Knowledge Graph completion

  • Few-Shot Knowledge Graph Completion

  • Relational Graph Neural Network with Hierarchical Attention for Knowledge Graph Completion

  • A Re-evaluation of Knowledge Graph Completion Methods

  • Translating Embedding with Local Connection for Knowledge Graph Completion

  • The Impact of Negative Triple Generation Strategies and Anomalies on Knowledge Graph Completion

  • Embedding based Link Prediction for Knowledge Graph Completion

  • GAEAT: Graph Auto-Encoder Attention Networks for Knowledge Graph Completion

  • Learning Physical Common Sense as Knowledge Graph Completion via BERT Data Augmentation and Constrained Tucker Factorization

  • Hyperbolic Knowledge Graph Embeddings for Knowledge Base Completion

  • Incremental Multi-source Entity Resolution for Knowledge Graph Completion

  • Dynamic Knowledge Graph Completion with Jointly Structural and Textual Dependency

  • PRTransE: Emphasize More Important Facts Based on Pagerank for Knowledge Graph Completion

  • RA-GCN: Relational Aggregation Graph Convolutional Network for Knowledge Graph Completion

  • Weighted Aggregator for the Open-World Knowledge Graph Completion

  • Multi-view Classification Model for Knowledge Graph Completion

  • A Re-Ranking Framework for Knowledge Graph Completion

  • A Contextualized Entity Representation for Knowledge Graph Completion

  • Duality-Induced Regularizer for Tensor Factorization Based Knowledge Graph Completion

  • MSGE: A Multi-step Gated Model for Knowledge Graph Completion

  • Realistic Re-evaluation of Knowledge Graph Completion Methods: An Experimental Study

  • Mining Implicit Entity Preference from User-Item Interaction Data for Knowledge Graph Completion via Adversarial Learning

  • Relation Adversarial Network for Low Resource Knowledge Graph Completion

  • Knowledge Graph Representation Learning With Multi-Scale Capsule-Based Embedding Model Incorporating Entity Descriptions

  • Reliable Knowledge Graph Path Representation Learning

  • A Model of Text-Enhanced Knowledge Graph Representation Learning With Mutual Attention

  • Representation Learning of Knowledge Graphs With Entity Attributes

  • Distributed representation of knowledge graphs with subgraph-aware proximity

  • 3D Learning and Reasoning in Link Prediction Over Knowledge Graphs

  • Reinforcement learning with actor-critic for knowledge graph reasoning

  • SDT: An integrated model for open-world knowledge graph reasoning

  • A review: Knowledge reasoning over knowledge graph

  • ADRL: An attention-based deep reinforcement learning framework for knowledge graph reasoning

  • Knowledge graphs completion via probabilistic reasoning

  • Path-based reasoning with constrained type attention for knowledge graph completion

  • Hybrid reasoning in knowledge graphs: Combing symbolic reasoning and statistical reasoning

  • ALSTM: An attention-based long short-term memory framework for knowledge base reasoning

  • Modeling of complex internal logic for knowledge base completion

  • Entity-related paths modeling for knowledge base completion

  • Integrated Embedding Approach for Knowledge Base Completion with CNN

  • Modeling relation paths for knowledge base completion via joint adversarial training

  • GRL: Knowledge graph completion with GAN-based reinforcement learning

  • Path-based reasoning with constrained type attention for knowledge graph completion

  • Tensor Graph Convolutional Networks for Multi-Relational and Robust Learning

  • 3D Learning and Reasoning in Link Prediction Over Knowledge Graphs

  • Benchmarking neural embeddings for link prediction in knowledge graphs under semantic and structural changes

  • Knowledge base enrichment by relation learning from social tagging data

  • Relation classification via knowledge graph enhanced transformer encoder

Conference

ICLR

  • (CompGCN) Shikhar Vashishth, Soumya Sanyal, Vikram Nitin, Partha Talukdar. "Composition-based Multi-Relational Graph Convolutional Networks". ICLR 2020. Cite 29. paper code 🔥

  • (Teach) Daniel Ruffinelli, Samuel Broscheit, Rainer Gemulla. "You CAN Teach an Old Dog New Tricks! On Training Knowledge Graph Embeddings". ICLR 2020. Cite 21. paper 🔥

  • (DrKIT) Bhuwan Dhingra, Manzil Zaheer, Vidhisha Balachandran, Graham Neubig, Ruslan Salakhutdinov, William W. Cohen. "Differentiable Reasoning over a Virtual Knowledge Base". ICLR 2020. Cite 19. paper 🔥

  • (Q2B) Hongyu Ren, Weihua Hu, Jure Leskovec. "Query2box: Reasoning over Knowledge Graphs in Vector Space Using Box Embeddings". ICLR 2020. Cite 17. paper 🔥

  • Pedro Tabacof, Luca Costabello. "Probability Calibration for Knowledge Graph Embedding Models". ICLR 2020. Cite 7. paper

  • (HypE) Bahare Fatemi, Perouz Taslakian, David Vazquez, David Poole. "Knowledge Hypergraphs: Prediction Beyond Binary Relations". ICLR 2020. Cite 6. paper

  • (TComplEx) Timothée Lacroix, Guillaume Obozinski, Nicolas Usunier. "Tensor Decompositions for Temporal Knowledge Base Completion". ICLR 2020. Cite 5. paper

  • (ReifKB) William W. Cohen, Haitian Sun, R. Alex Hofer, Matthew Siegler. "Scalable Neural Methods for Reasoning With a Symbolic Knowledge Base". ICLR 2020. Cite 3. paper

  • (DPMPN) Xiaoran Xu, Wei Feng, Yunsheng Jiang, Xiaohui Xie, Zhiqing Sun, Zhi-Hong Deng. "Dynamically Pruned Message Passing Networks for Large-scale Knowledge Graph Reasoning". ICLR 2020. Cite 3. paper code

  • (Neural-LP-N) Po-Wei Wang, Daria Stepanova, Csaba Domokos, J. Zico Kolter. "Differentiable learning of numerical rules in knowledge graphs". ICLR 2020. Cite 1. paper

NeurIPS
  • (GEN) Jinheon Baek, Dong Bok Lee, Sung Ju Hwang. "Learning to Extrapolate Knowledge: Transductive Few-shot Out-of-Graph Link Prediction". NeurIPS 2020. paper code
ICML
  • (LowFER) Saadullah Amin, Stalin Varanasi, Katherine Ann Dunfield, Günter Neumann. "LowFER: Low-rank Bilinear Pooling for Link Prediction". ICML 2020. CCF A. Cite 0. paper
AAAI

  • (DE-SimplE) Rishab Goel, Seyed Mehran Kazemi, Marcus Brubaker, Pascal Poupart. "Diachronic Embedding for Temporal Knowledge Graph Completion". AAAI 2020. CCF A. Cite 19. paper code 🔥

  • (GNTPs) Pasquale Minervini, Matko Bosnjak, Tim Rocktäschel, Sebastian Riedel, Edward Grefenstette. "Differentiable Reasoning on Large Knowledge Bases and Natural Language". AAAI 2020. CCF A. Cite 19. paper 🔥

  • (InteractE) Shikhar Vashishth, Soumya Sanyal, Vikram Nitin, Nilesh Agrawal, Partha Talukdar. "InteractE: Improving Convolution-based Knowledge Graph Embeddings by Increasing Feature Interactions". AAAI 2020. CCF A. Cite 18. paper code supp 🔥

  • (HAKE) Zhanqiu Zhang, Jianyu Cai, Yongdong Zhang, Jie Wang. "Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Prediction". AAAI 2020. CCF A. Cite 12. paper code 🔥

  • Chaitanya Malaviya, Chandra Bhagavatula, Antoine Bosselut, Yejin Choi. "Commonsense Knowledge Base Completion with Structural and Semantic Context". AAAI 2020. CCF A. Cite 11. paper 🔥

  • (FSRL) Chuxu Zhang, Huaxiu Yao, Chao Huang, Meng Jiang, Zhenhui Li, Nitesh V. Chawla. "Few-Shot Knowledge Graph Completion". AAAI 2020. paper code

  • (RPJE) Guanglin Niu, Yongfei Zhang, Bo Li, Peng Cui, Si Liu, Jingyang Li, Xiaowei Zhang. "Rule-Guided Compositional Representation Learning on Knowledge Graphs". AAAI 2020. CCF A. Cite 6. paper

  • (ZSGAN) Pengda Qin, Xin Wang, Wenhu Chen, Chunyun Zhang, Weiran Xu, William Yang Wang. "Generative Adversarial Zero-Shot Relational Learning for Knowledge Graphs". AAAI 2020. paper code

  • (R2D2) Marcel Hildebrandt, Jorge Andres Quintero Serna, Yunpu Ma, Martin Ringsquandl, Mitchell Joblin, Volker Tresp. "Reasoning on Knowledge Graphs with Debate Dynamics". AAAI 2020. CCF A. Cite 4. paper

  • Zhao Zhang, Fuzhen Zhuang, Hengshu Zhu, Zhiping Shi, Hui Xiong, Qing He. "Relational Graph Neural Network with Hierarchical Attention for Knowledge Graph Completion". AAAI 2020. CCF A. Cite 2. paper

  • Peru Bhardwaj. "Towards Adversarially Robust Knowledge Graph Embeddings. AAAI 2020. CCF A. Cite 1. paper

  • Feihu Che, Dawei Zhang, Jianhua Tao, Mingyue Niu, Bocheng Zhao. "ParamE: Regarding Neural Network Parameters as Relation Embeddings for Knowledge Graph Completion". AAAI 2020. CCF A. Cite 1. paper

  • George Stoica, Otilia Stretcu, Anthony Platanios, Tom Mitchell, Barnabas Poczos. "Contextual Parameter Generation for Knowledge Graph Link Prediction". AAAI 2020. CCF A. Cite 0. paper

IJCAI
EMNLP

  • Prachi Jain, Sushant Rathi, Mausam, Soumen Chakrabarti. "Temporal Knowledge Base Completion: New Algorithms and Evaluation Protocols". EMNLP 2020. paper

  • (FAAN) Jiawei Sheng, Shu Guo, Zhenyu Chen, Juwei Yue, Lihong Wang, Tingwen Liu, Hongbo Xu. "Adaptive Attentional Network for Few-Shot Knowledge Graph Completion". EMNLP 2020. paper code

  • (FIRE) Chuxu Zhang, Lu Yu, Mandana Saebi, Meng Jiang, Nitesh V. Chawla. "Few-Shot Multi-Hop Relation Reasoning over Knowledge Bases". EMNLP (Findings) 2020. paper

Lapse

  • (DArtNet) Sankalp Garg, Navodita Sharma, Woojeong Jin, Xiang Ren. "Temporal Attribute Prediction via Joint Modeling of Multi-Relational Structure Evolution". IJCAI 2020. CCF A. Cite 1. paper code

  • Fuxiang Zhang, Xin Wang, Zhao Li, Jianxin Li. "TransRHS: A Representation Learning Method for Knowledge Graphs with Relation Hierarchical Structure". IJCAI 2020. CCF A. Cite 0. paper

  • Zhiqing Sun, Shikhar Vashishth, Soumya Sanyal, Partha Talukdar and Yiming Yang. "A Re-evaluation of Knowledge Graph Completion Methods". ACL 2020. CCF A. Cite 16. paper 🔥

  • Ines Chami, Adva Wolf, Da-Cheng Juan, Frederic Sala, Sujith Ravi and Christopher Ré. "Low-Dimensional Hyperbolic Knowledge Graph Embeddings". ACL 2020. CCF A. Cite 7. paper

  • Yun Tang, Jing Huang, Guangtao Wang, Xiaodong He, Bowen Zhou. "Orthogonal Relation Transforms with Graph Context Modeling for Knowledge Graph Embedding". ACL 2020. CCF A. Cite 6. paper

  • Mrinmaya Sachan. "Knowledge Graph Embedding Compression". ACL 2020. CCF A. Cite 2. paper

  • Wentao Xu, Shun Zheng, Liang He, Bin Shao, Jian Yin and Tie-Yan Liu. "SEEK: Segmented Embedding of Knowledge Graphs". ACL 2020. CCF A. Cite 2. paper

  • Samuel Broscheit, Kiril Gashteovski, Yanjie Wang, Rainer Gemulla. "Can We Predict New Facts with Open Knowledge Graph Embeddings? A Benchmark for Open Link Prediction". ACL 2020. CCF A. Cite 2. paper

  • Zhiwen Xie, Guangyou Zhou, Jin Liu and Jimmy Xiangji Huang. "ReInceptionE: Relation-Aware Inception Network with Joint Local-Global Structural Information for Knowledge Graph Embedding". ACL 2020. CCF A. Cite 1. paper

  • Yu Zhao, anxiang zhang, Ruobing Xie, Kang Liu and Xiaojie WANG. "Connecting Embeddings for Knowledge Graph Entity Typing". ACL 2020. CCF A. Cite 0. paper

  • Farahnaz Akrami, Mohammed Samiul Saeef, Qingheng Zhang, Wei Hu, Chengkai Li. "Realistic Re-evaluation of Knowledge Graph Completion Methods: An Experimental Study". SIGMOD 2020. CCF A. Cite 10. paper

  • Yongqi Zhang, Quanming Yao, Wenyuan Dai, Lei Chen. "AutoSF: Searching Scoring Functions for Knowledge Graph Embedding". ICDE 2020. CCF A. Cite 5. paper

  • Paolo Rosso, Dingqi Yang, Philippe Cudré-Mauroux. "Beyond Triplets: Hyper-Relational Knowledge Graph Embedding for Link Prediction". WWW 2020. CCF A. Cite 5. paper

  • Jiaoyan Chen, Xi Chen, Ian Horrocks, Ernesto Jiménez-Ruiz, Erik B. Myklebust. "Correcting Knowledge Base Assertions". WWW 2020. CCF A. Cite 3. paper

  • Unmesh Joshi, Jacopo Urbani. "Searching for Embeddings in a Haystack: Link Prediction on Knowledge Graphs with Subgraph Pruning". WWW 2020. CCF A. Cite 0. paper

  • Aisha Mohamed, Shameem Puthiya Parambath, Zoi Kaoudi, Ashraf Aboulnaga. "Popularity Agnostic Evaluation of Knowledge Graph Embeddings". UAI 2020. CCF B. Cite 0. paper

  • Tong Yang, Long Sha, Pengyu Hong. "NagE: Non-Abelian Group Embedding for Knowledge Graphs". CIKM 2020. CCF B. Cite 1. paper

  • Iti Bansal, Sudhanshu Tiwari, Carlos R. Rivero. "The Impact of Negative Triple Generation Strategies and Anomalies on Knowledge Graph Completion". CIKM 2020. CCF B. Cite 0. paper

  • Chang Gao, Chengjie Sun, Lili Shan, Lei Lin, Mingjiang Wang. "Rotate3D: Representing Relations as Rotations in Three-Dimensional Space for Knowledge Graph Embedding". CIKM 2020. CCF B. Cite 0. paper

  • Garima Gaur, Arnab Bhattacharya, Srikanta Bedathur. "How and Why is An Answer (Still) Correct? Maintaining Provenance in Dynamic Knowledge Graphs". CIKM 2020. CCF B. Cite 0. paper

  • Shu Guo, Lin Li, Zhen Hui, Lingshuai Meng, Bingnan Ma, Wei Liu, Lihong Wang, Haibin Zhai, Hong Zhang. "Knowledge Graph Embedding Preserving Soft Logical Regularity". CIKM 2020. CCF B. Cite 0. paper

  • Julien Leblay, Melisachew Wudage Chekol, Xin Liu. "Towards Temporal Knowledge Graph Embeddings with Arbitrary Time Precision". CIKM 2020. CCF B. Cite 0. paper

  • Yanfei Han, Quan Fang, Jun Hu, Shengsheng Qian, Changsheng Xu. "GAEAT: Graph Auto-Encoder Attention Networks for Knowledge Graph Completion". CIKM 2020. CCF B. Cite 0. paper

  • Xiaoyu Kou, Bingfeng Luo, Huang Hu, Yan Zhang. "NASE: Learning Knowledge Graph Embedding for Link Prediction via Neural Architecture Search". CIKM 2020. CCF B. Cite 0. paper

  • Russa Biswas. "Embedding based Link Prediction for Knowledge Graph Completion". CIKM 2020. CCF B. Cite 0. paper

  • Zeyuan Cui, Shijun Liu, Li Pan, Qiang He. "Translating Embedding with Local Connection for Knowledge Graph Completion". AAMAS 2020. CCF B. Cite 0. paper

  • Da Xu, Chuanwei Ruan, Jason Cho, Evren Körpeoglu, Sushant Kumar, Kannan Achan. "Knowledge-aware Complementary Product Representation Learning". CCF B. WSDM 2020. Cite 1. paper

  • Thomas Pellissier Tanon, Gerhard Weikum, Fabian M. Suchanek. "YAGO 4: A Reason-able Knowledge Base. ESWC 2020. CCF C. Cite 8. paper

  • Prodromos Kolyvakis, Alexandros Kalousis, Dimitris Kiritsis. "Hyperbolic Knowledge Graph Embeddings for Knowledge Base Completion". ESWC 2020. CCF C. Cite 1. paper

  • Giorgos Stoilos , Damir Juric, Szymon Wartak, Claudia Schulz , Mohammad Khodadadi. "Hybrid Reasoning Over Large Knowledge Bases Using On-The-Fly Knowledge Extraction". ESWC 2020. CCF C. Cite 0.paper

  • Ningning Jia, Xiang Cheng, Sen Su. "Improving Knowledge Graph Embedding Using Locally and Globally Attentive Relation Paths". ECIR 2020. CCF C. Cite 0. paper

  • Chunyang Tan, Kaijia Yang, Xinyu Dai, Shujian Huang, Jiajun Chen. "MSGE: A Multi-step Gated Model for Knowledge Graph Completion". PAKDD 2020. CCF C. Cite 0. paper

  • Varun Ranganathan, Siddharth Suresh, Yash Mathur, Natarajan Subramanyam, Denilson Barbosa. "GrCluster: a score function to model hierarchy in knowledge graph embeddings". SAC 2020. CCF C. Cite 0. paper

  • Chenjin Xu, Mojtaba Nayyeri, Fouad Alkhoury, Hamed Shariat Yazdi, Jens Lehmann. "Temporal Knowledge Graph Completion Based on Time Series Gaussian Embedding". ISWC. CCF B. paper

  • Chengjin Xu, Mojtaba Nayyeri, Fouad Alkhoury, Hamed Shariat Yazdi, Jens Lehmann. "TeRo: A Time-aware Knowledge Graph Embedding via Temporal Rotation". COLING 2020. CCF B. paper

  • Liang Qu, Huaisheng Zhu, Qiqi Duan, Yuhui Shi. "Continuous-Time Link Prediction via Temporal Dependent Graph Neural Network". WWW 2020. CCF A. paper

  • Jiasheng Zhang, Yongpan Sheng, Zheng Wang, Jie Shao. "TKGFrame: A Two-Phase Framework for Temporal-Aware Knowledge Graph Completion". APWeb/WAIM 2020. CCF B. paper

  • Lifan Lin, Kun She. "Tensor Decomposition-Based Temporal Knowledge Graph Embedding". ICTAI 2020. CCF C. paper

  • Haoyu Wang, Vivek Kulkarni, William Yang Wang. "Dolores: Deep Contextualized Knowledge Graph Embeddings". AKBC 2020. paper

  • Hao Huang, Guodong Long, Tao Shen, Jing Jiang, Chengqi Zhang. "RatE: Relation-Adaptive Translating Embedding for Knowledge Graph Completion". COLING 2020. paper

  • Yuzhang Liu, Peng Wang, Yingtai Li, Yizhan Shao, Zhongkai Xu. "AprilE: Attention with Pseudo Residual Connection for Knowledge Graph Embedding". COLING 2020. paper

  • Yuxin Zhang, Bohan Li, Han Gao, Ye Ji, Han Yang, Meng Wang. "Fine-Grained Evaluation of Knowledge Graph Embedding Models in Downstream Tasks". APWeb/WAIM 2020. paper

  • Feiliang Ren, Juchen Li, Huihui Zhang, Shilei Liu, Bochao Li, Ruicheng Ming, Yujia Bai. "Knowledge Graph Embedding with Atrous Convolution and Residual Learning". COLING 2020. paper

  • Chengjin Xu, Mojtaba Nayyeri, Yung-Yu Chen, Jens Lehmann. "Knowledge Graph Embeddings in Geometric Algebras". COLING 2020. paper

  • Sicong Dong, Xin Wang, Lele Chai, Jianxin Li, Yajun Yang. "PDKE: An Efficient Distributed Embedding Framework for Large Knowledge Graphs". DASFAA 2020. paper

  • Yunfeng Li, Xiaoyong Li, Mingjian Lei. "CTransE: An Effective Information Credibility Evaluation Method Based on Classified Translating Embedding in Knowledge Graphs". DEXA 2020. paper

  • Chenchen Li, Aiping Li, Hongkui Tu, Ye Wang, Changhai Wang. "A Knowledge Graph Embedding Method Based on Neural Network". DSC 2020. paper

  • Tao Luo, Yifan Wei, Mei Yu, Xuewei Li, Mankun Zhao, Tianyi Xu, Jian Yu, Jie Gao, Ruiguo Yu. "BTDE: Block Term Decomposition Embedding for Link Prediction in Knowledge Graph". ECAI 2020. paper

  • Afshin Sadeghi, Damien Graux, Hamed Shariat Yazdi, Jens Lehmann. "MDE: Multiple Distance Embeddings for Link Prediction in Knowledge Graphs". ECAI 2020. paper

  • Hung Nghiep Tran, Atsuhiro Takasu. "Multi-Partition Embedding Interaction with Block Term Format for Knowledge Graph Completion". ECAI 2020. paper

  • Meng Wang, Tongtong Wu, Guilin Qi. "A Hash Learning Framework for Search-Oriented Knowledge Graph Embedding". ECAI 2020. paper

  • Ningning Jia, Xiang Cheng, Sen Su. "Improving Knowledge Graph Embedding Using Locally and Globally Attentive Relation Paths". ECIR 2020. paper

  • Joseph Fisher, Arpit Mittal, Dave Palfrey, Christos Christodoulopoulos. "Debiasing knowledge graph embeddings". EMNLP 2020. paper

  • A Greedy Bit-flip Training Algorithm for Binarized Knowledge Graph Embeddings

  • AutoETER: Automated Entity Type Representation with Relation-Aware Attention for Knowledge Graph Embedding

  • Evaluating the Calibration of Knowledge Graph Embeddings for Trustworthy Link Prediction

  • Knowledge Association with Hyperbolic Knowledge Graph Embeddings

  • Affinity Dependent Negative Sampling for Knowledge Graph Embeddings

  • Conditional Constraints for Knowledge Graph Embeddings

  • Knowledge Graph Embedding Based on Relevance and Inner Sequence of Relations

  • Neighborhood Aggregation Embedding Model for Link Prediction in Knowledge Graphs

  • KGvec2go - Knowledge Graph Embeddings as a Service

  • Beta Embeddings for Multi-Hop Logical Reasoning in Knowledge Graphs.

  • Interstellar: Searching Recurrent Architecture for Knowledge Graph Embedding

  • GrCluster: a score function to model hierarchy in knowledge graph embeddings

  • ExCut: Explainable Embedding-Based Clustering over Knowledge Graphs

  • Fantastic Knowledge Graph Embeddings and How to Find the Right Space for Them

  • DGL-KE: Training Knowledge Graph Embeddings at Scale

  • Popularity Agnostic Evaluation of Knowledge Graph Embeddings

  • TransMVG: Knowledge Graph Embedding Based on Multiple-Valued Gates

  • Searching for Embeddings in a Haystack: Link Prediction on Knowledge Graphs with Subgraph Pruning

  • Beyond Triplets: Hyper-Relational Knowledge Graph Embedding for Link Prediction

  • Rule-Guided Compositional Representation Learning on Knowledge Graphs

  • Rotate3D: Representing Relations as Rotations in Three-Dimensional Space for Knowledge Graph Embedding

  • TransRHS: A Representation Learning Method for Knowledge Graphs with Relation Hierarchical Structure

  • A Contextualized Entity Representation for Knowledge Graph Completion

  • BCRL: Long Text Friendly Knowledge Graph Representation Learning

  • Differentiable Reasoning on Large Knowledge Bases and Natural Language

  • Few-Shot Multi-Hop Relation Reasoning over Knowledge Bases

  • Hybrid Reasoning Over Large Knowledge Bases Using On-The-Fly Knowledge Extraction

  • Scalable Neural Methods for Reasoning With a Symbolic Knowledge Base

  • Sequential Fuzzy Description Logic: Reasoning for Fuzzy Knowledge Bases with Sequential Information

  • Bridging Text and Knowledge with Multi-Prototype Embedding for Few-Shot Relational Triple Extraction

  • Semi-Supervised Learning of Processes Over Multi-Relational Graphs

  • Composition-based Multi-Relational Graph Convolutional Networks

  • MR-GCN: Multi-Relational Graph Convolutional Networks based on Generalized Tensor Product

  • Neural Message Passing for Multi-Relational Ordered and Recursive Hypergraphs

  • EvolveGraph: Multi-Agent Trajectory Prediction with Dynamic Relational Reasoning

  • The Research of Link Prediction in Knowledge Graph based on Distance Constraint

  • A Multi-Scale Approach for Graph Link Prediction

  • Contextual Parameter Generation for Knowledge Graph Link Prediction

  • Link Prediction between Group Entities in Knowledge Graphs

  • Can We Predict New Facts with Open Knowledge Graph Embeddings? A Benchmark for Open Link Prediction

  • Exploiting Common Neighbor Graph for Link Prediction

  • Link Prediction: A Graphical Model Approach

  • Neighborhood Aggregation Embedding Model for Link Prediction in Knowledge Graphs

  • Learning to Extrapolate Knowledge: Transductive Few-shot Out-of-Graph Link Prediction

  • Link prediction via community detection in bipartite multi-layer graphs

  • Interpreting Link Prediction on Knowledge Graphs

  • Explainable Link Prediction for Emerging Entities in Knowledge Graphs

  • Searching for Embeddings in a Haystack: Link Prediction on Knowledge Graphs with Subgraph Pruning

  • Beyond Triplets: Hyper-Relational Knowledge Graph Embedding for Link Prediction

  • Contextual Parameter Generation for Knowledge Graph Link Prediction

  • BTDE: Block Term Decomposition Embedding for Link Prediction in Knowledge Graph

  • Evaluating the Calibration of Knowledge Graph Embeddings for Trustworthy Link Prediction

  • Neighborhood Aggregation Embedding Model for Link Prediction in Knowledge Graphs

  • Learning to Extrapolate Knowledge: Transductive Few-shot Out-of-Graph Link Prediction

  • Interpreting Link Prediction on Knowledge Graphs

  • Explainable Link Prediction for Emerging Entities in Knowledge Graphs

  • Beyond Triplets: Hyper-Relational Knowledge Graph Embedding for Link Prediction

  • Dynamic Anticipation and Completion for Multi-Hop Reasoning over Sparse Knowledge Graph

  • Dynamic Knowledge Graph Completion with Jointly Structural and Textual Dependency

  • Modeling Relation Path for Knowledge Graph via Dynamic Projection

  • Generalizing Tensor Decomposition for N-ary Relational Knowledge Bases

  • Generative Adversarial Zero-Shot Relational Learning for Knowledge Graphs

  • Relational Graph Neural Network with Hierarchical Attention for Knowledge Graph Completion

Arxiv

  • Yunpu Ma, Yuyi Wang, Volker Tresp. "Quantum Machine Learning Algorithm for Knowledge Graphs". CoRR 2020-01. Cite 0. paper

  • Andrea Rossi, Donatella Firmani, Antonio Matinata, Paolo Merialdo, Denilson Barbosa. "Knowledge Graph Embedding for Link Prediction: A Comparative Analysis". CoRR 2020-02. Cite 4. paper

  • Jianyu Liu, Hegler Tissot. "Clustering as an Evaluation Protocol for Knowledge Embedding Representation of Categorised Multi-relational Data in the Clinical Domain". CoRR 2020-02. Cite 0. paper

  • Vassilis N. Ioannidis, Antonio G. Marques, Georgios B. Giannakis. "Tensor Graph Convolutional Networks for Multi-relational and Robust Learning". CoRR 2020-03. Cite 0. paper

  • Marjan Albooyeh, Rishab Goel, Seyed Mehran Kazemi. "Out-of-Sample Representation Learning for Multi-Relational Graphs". CoRR 2020-04. Cite 1. paper

  • Yanhui Peng, Jing Zhang. "Knowledge Graph Embedding with Linear Representation for Link Prediction". CoRR 2020-04. Cite 0. paper

  • Bishal Santra, Prakhar Sharma, Sumegh Roychowdhury, Pawan Goyal. "Exploring Effects of Random Walk Based Minibatch Selection Policy on Knowledge Graph Completion". CoRR 2020-04. Cite 0. paper

  • Rajarshi Bhowmik, Gerard de Melo. "A Joint Framework for Inductive Representation Learning and Explainable Reasoning in Knowledge Graphs". CoRR 2020-05. Cite 0. paper

  • Asan Agibetov, Matthias Samwald. "Benchmarking neural embeddings for link prediction in knowledge graphs under semantic and structural changes". CoRR 2020-05. Cite 0. paper

  • Rajarshi Das, Ameya Godbole, Shehzaad Dhuliawala, Manzil Zaheer, Andrew McCallum. "A Simple Approach to Case-Based Reasoning in Knowledge Bases". CoRR 2020-06. Cite 0. paper

  • Zhen Han, Peng Chen, Yunpu Ma, Volker Tresp. "DyERNIE: Dynamic Evolution of Riemannian Manifold Embeddings for Temporal Knowledge Graph Completion". EMNLP 2020. CCF B. paper

  • Reasoning on Knowledge Graphs with Debate Dynamics.

  • Learning Collaborative Agents with Rule Guidance for Knowledge Graph Reasoning

  • Dynamic Anticipation and Completion for Multi-Hop Reasoning over Sparse Knowledge Graph

  • MCMH: Learning Multi-Chain Multi-Hop Rules for Knowledge Graph Reasoning

  • Neural-Symbolic Relational Reasoning on Graph Models: Effective Link Inference and Computation from Knowledge Bases

  • Dynamically Pruned Message Passing Networks for Large-scale Knowledge Graph Reasoning

  • Reasoning Like Human: Hierarchical Reinforcement Learning for Knowledge Graph Reasoning

  • Commonsense Knowledge Base Completion with Structural and Semantic Context

  • OxKBC: Outcome Explanation for Factorization Based Knowledge Base Completion

  • Revisiting Evaluation of Knowledge Base Completion Models

  • Ranking vs. Classifying: Measuring Knowledge Base Completion Quality

  • Embedding based Link Prediction for Knowledge Graph Completion

  • IntKB: A Verifiable Interactive Framework for Knowledge Base Completion

  • Hyperbolic Knowledge Graph Embeddings for Knowledge Base Completion

  • PRTransE: Emphasize More Important Facts Based on Pagerank for Knowledge Graph Completion

  • Knowledge Base Completion for Constructing Problem-Oriented Medical Records

  • BoxE: A Box Embedding Model for Knowledge Base Completion

  • Duality-Induced Regularizer for Tensor Factorization Based Knowledge Graph Completion

  • Modeling Relation Path for Knowledge Graph via Dynamic Projection

Datasets

Standard

Rule

Text

Temporal

Performance

Link Prediction

ICEWS14

Year Source Methods MR MRR Hits@1 Hits@3 Hits@10
2018 EMNLP TA-DistMult 276 0.477 0.363 - 0.686
2018 EMNLP HyTEDE-SinplE - 0.297 0.108 0.416 0.655
2020 AAAI DE-TransE - 0.326 0.124 0.467 0.686
2020 AAAI DE-DistMult - 0.501 0.392 0.569 0.708
2020 AAAI DE-SimplE - 0.526 0.418 0.592 0.725
2020 ICLR TNTComplEx - 0.56 0.46 0.61 0.74

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