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Must-read papers on knowledge representation learning (KRL) / knowledge embedding (KE)

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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

  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

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Must-read papers on knowledge representation learning (KRL) / knowledge embedding (KE)

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