Must-read papers on KRL/KE.

KRL: knowledge representation learning. KE: knowledge embedding.

Contributed by Shulin Cao and Xu Han.

We release OpenKE, an open source toolkit for KRL/KE. This repository provides a standard KRL/KE training and testing framework. Currently, the implemented models in OpenKE include TransE, TransH, TransR, TransD, RESCAL, DistMult, ComplEx and HolE.

Survey papers:

1. Representation Learning: A Review and New Perspectives. Yoshua Bengio, Aaron Courville, and Pascal Vincent. IEEE 2013. paper

2. Knowledge Representation Learning: A Review. (In Chinese) Zhiyuan Liu, Maosong Sun, Yankai Lin, Ruobing Xie. 2016. paper

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

4. Knowledge Graph Embedding: A Survey of Approaches and Applications. Quan Wang, Zhendong Mao, Bin Wang, Li Guo. IEEE 2017. paper

Journal and Conference papers:

1. RESCAL: A Three-Way Model for Collective Learning on Multi-Relational Data. Nickel Maximilian, Tresp Volker, Kriegel Hans-Peter. ICML 2011. paper code

2. SE: Learning Structured Embeddings of Knowledge Bases. Antoine Bordes, Jason Weston, Ronan Collobert, Yoshua Bengio. AAAI 2011. paper

3. LFM: A Latent Factor Model for Highly Multi-relational Data. Rodolphe Jenatton, Nicolas L. Roux, Antoine Bordes, Guillaume R. Obozinski. NIPS 2012. paper

4. NTN: Reasoning With Neural Tensor Networks for Knowledge Base Completion. Richard Socher, Danqi Chen, Christopher D. Manning, Andrew Ng. NIPS 2013. paper

5. TransE: Translating Embeddings for Modeling Multi-relational Data. Antoine Bordes, Nicolas Usunier, Alberto Garcia-Duran, Jason Weston, Oksana Yakhnenko. NIPS 2013. paper code

6. TransH: Knowledge Graph Embedding by Translating on Hyperplanes. Zhen Wang, Jianwen Zhang, Jianlin Feng, Zheng Chen. AAAI 2014. paper code

7. TransR & CTransR: Learning Entity and Relation Embeddings for Knowledge Graph Completion. Yankai Lin, Zhiyuan Liu, Maosong Sun, Yang Liu, Xuan Zhu. AAAI 2015. paper KB2E OpenKE

8. TransD: Knowledge Graph Embedding via Dynamic Mapping Matrix. Guoliang Ji, Shizhu He, Liheng Xu, Kang Liu, Jun Zhao. ACL 2015. paper KB2E OpenKE

9. TransA: An Adaptive Approach for Knowledge Graph Embedding. Han Xiao, Minlie Huang, Hao Yu, Xiaoyan Zhu. arXiv 2015. paper

10. KG2E: Learning to Represent Knowledge Graphs with Gaussian Embedding. Shizhu He, Kang Liu, Guoliang Ji and Jun Zhao. CIKM 2015. paper code

11. DistMult: Embedding Entities and Relations for Learning and Inference in Knowledge Bases. Bishan Yang, Wen-tau Yih, Xiaodong He, Jianfeng Gao, Li Deng. ICLR 2015. paper code

12. PTransE: Modeling Relation Paths for Representation Learning of Knowledge Bases. Yankai Lin, Zhiyuan Liu, Huanbo Luan, Maosong Sun, Siwei Rao, Song Liu. EMNLP 2015. paper code

13. RTransE: Composing Relationships with Translations. Alberto García-Durán, Antoine Bordes, Nicolas Usunier. EMNLP 2015. paper

14. ManifoldE: From One Point to A Manifold: Knowledge Graph Embedding For Precise Link Prediction. Han Xiao, Minlie Huang and Xiaoyan Zhu. IJCAI 2016. paper

15. TransG: A Generative Mixture Model for Knowledge Graph Embedding. Han Xiao, Minlie Huang, Xiaoyan Zhu. ACL 2016. paper code

16. ComplEx: Complex Embeddings for Simple Link Prediction. Théo Trouillon, Johannes Welbl, Sebastian Riedel, Éric Gaussier and Guillaume Bouchard. ICML 2016. paper code OpenKE

17. HolE: Holographic Embeddings of Knowledge Graphs. Maximilian Nickel, Lorenzo Rosasco, Tomaso A. Poggio. AAAI 2016. paper code OpenKE

18. KR-EAR: Knowledge Representation Learning with Entities, Attributes and Relations. Yankai Lin, Zhiyuan Liu, Maosong Sun. IJCAI 2016. paper code

19. TranSparse: Knowledge Graph Completion with Adaptive Sparse Transfer Matrix. Guoliang Ji, Kang Liu, Shizhu He, Jun Zhao. AAAI 2016. paper code

20. TKRL: Representation Learning of Knowledge Graphs with Hierarchical Types. Ruobing Xie, Zhiyuan Liu, Maosong Sun. IJCAI 2016. paper code

21. STransE: A Novel Embedding Model of Entities and Relationships in Knowledge Bases. Dat Quoc Nguyen, Kairit Sirts, Lizhen Qu and Mark Johnson. NAACL-HLT 2016. paper code

22. GAKE: Graph Aware Knowledge Embedding. Jun Feng, Minlie Huang, Yang Yang, Xiaoyan Zhu. COLING 2016. paper code

23. DKRL: Representation Learning of Knowledge Graphs with Entity Descriptions. Ruobing Xie, Zhiyuan Liu, Jia Jia, Huanbo Luan, Maosong Sun. AAAI 2016. paper code

24. ProPPR: Learning First-Order Logic Embeddings via Matrix Factorization. William Yang Wang, William W. Cohen. IJCI 2016. paper

25. SSP: Semantic Space Projection for Knowledge Graph Embedding with Text Descriptions. Han Xiao, Minlie Huang, Lian Meng, Xiaoyan Zhu. AAAI 2017. paper

26. ProjE: Embedding Projection for Knowledge Graph Completion. Baoxu Shi, Tim Weninger. AAAI 2017. paper code

27. ANALOGY: Analogical Inference for Multi-relational Embeddings. Hanxiao Liu, Yuexin Wu, Yiming Yang. ICML 2017. paper code

28. IKRL: Image-embodied Knowledge Representation Learning. Ruobing Xie, Zhiyuan Liu, Tat-Seng Chua, Huan-Bo Luan, Maosong Sun. IJCAI 2017. paper code

29. IPTransE: Iterative Entity Alignment via Joint Knowledge Embeddings. Hao Zhu, Ruobing Xie, Zhiyuan Liu, Maosong Sun. IJCAI 2017. paper code

30. On the Equivalence of Holographic and Complex Embeddings for Link Prediction. Katsuhiko Hayashi, Masashi Shimbo. ACL 2017. paper