Must-read papers on KRL/KE
KRL:Knowledge Representation Learning KE:Knowledge Embedding
綜述類（Survey papers）：
1.Representation Learning: A Review and New Perspectives. Yoshua Bengio, Aaron Courville, and Pascal Vincent.TPAMI 2013.
2.Knowledge Representation Learning: A Review.(知識表示學習研究進展) (In Chinese) Zhiyuan Liu, Maosong Sun, Yankai Lin, Ruobing Xie.
3.A Review of Relational Machine Learning for Knowledge Graphs. Maximilian Nickel, Kevin Murphy, Volker Tresp, Evgeniy Gabrilovich. Proceedings of the IEEE 2016.
4.Knowledge Graph Embedding: A Survey of Approaches and Applications. Quan Wang, Zhendong Mao, Bin Wang, Li Guo. TKDE 2017.
期刊類（Journal and Conference papers）：
1.ESCAL: A Three-Way Model for Collective Learning on Multi-Relational Data. Nickel Maximilian, Tresp Volker, Kriegel Hans-Peter. ICML 2011.
2.SE: Learning Structured Embeddings of Knowledge Bases. Antoine Bordes, Jason Weston, Ronan Collobert, Yoshua Bengio. AAAI 2011.
3.LFM: A Latent Factor Model for Highly Multi-relational Data. Rodolphe Jenatton, Nicolas L. Roux, Antoine Bordes, Guillaume R. Obozinski. NIPS 2012.
4.NTN: Reasoning With Neural Tensor Networks for Knowledge Base Completion. Richard Socher, Danqi Chen, Christopher D. Manning, Andrew Ng. NIPS 2013.
5.TransE: Translating Embeddings for Modeling Multi-relational Data. Antoine Bordes, Nicolas Usunier, Alberto Garcia-Duran, Jason Weston, Oksana Yakhnenko. NIPS 2013.
6.TransH: Knowledge Graph Embedding by Translating on Hyperplanes. Zhen Wang, Jianwen Zhang, Jianlin Feng, Zheng Chen. AAAI 2014.
7.TransR & CTransR: Learning Entity and Relation Embeddings for Knowledge Graph Completion. Yankai Lin, Zhiyuan Liu, Maosong Sun, Yang Liu, Xuan Zhu. AAAI 2015.
8.TransD: Knowledge Graph Embedding via Dynamic Mapping Matrix. Guoliang Ji, Shizhu He, Liheng Xu, Kang Liu, Jun Zhao. ACL 2015.
9.TransA: An Adaptive Approach for Knowledge Graph Embedding. Han Xiao, Minlie Huang, Hao Yu, Xiaoyan Zhu.arXiv 2015.
10.KG2E: Learning to Represent Knowledge Graphs with Gaussian Embedding. Shizhu He, Kang Liu, Guoliang Ji and Jun Zhao. CIKM 2015.
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.
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.
13.RTransE: Composing Relationships with Translations. Alberto García-Durán, Antoine Bordes, Nicolas Usunier.EMNLP 2015.
14.ManifoldE: From One Point to A Manifold: Knowledge Graph Embedding For Precise Link Prediction. Han Xiao, Minlie Huang and Xiaoyan Zhu. IJCAI 2016.
15.TransG: A Generative Mixture Model for Knowledge Graph Embedding. Han Xiao, Minlie Huang, Xiaoyan Zhu.ACL 2016.
16.ComplEx: Complex Embeddings for Simple Link Prediction. Théo Trouillon, Johannes Welbl, Sebastian Riedel, Éric Gaussier and Guillaume Bouchard. ICML 2016.
17.ComplEx extension: Knowledge Graph Completion via Complex Tensor Factorization. Théo Trouillon, Christopher R. Dance, Johannes Welbl, Sebastian Riedel, Éric Gaussier, Guillaume Bouchard. JMLR 2017.
18.HolE: Holographic Embeddings of Knowledge Graphs. Maximilian Nickel, Lorenzo Rosasco, Tomaso A. Poggio.AAAI 2016.
19.KR-EAR: Knowledge Representation Learning with Entities, Attributes and Relations. Yankai Lin, Zhiyuan Liu, Maosong Sun. IJCAI 2016.
20.TranSparse: Knowledge Graph Completion with Adaptive Sparse Transfer Matrix. Guoliang Ji, Kang Liu, Shizhu He, Jun Zhao. AAAI 2016.
21.TKRL: Representation Learning of Knowledge Graphs with Hierarchical Types. Ruobing Xie, Zhiyuan Liu, Maosong Sun. IJCAI 2016.
22.TEKE: Text-Enhanced Representation Learning for Knowledge Graph. Zhigang Wang, Juan-Zi Li. IJCAI 2016.
23.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.
24.GAKE: Graph Aware Knowledge Embedding. Jun Feng, Minlie Huang, Yang Yang, Xiaoyan Zhu. COLING 2016.
25.DKRL: Representation Learning of Knowledge Graphs with Entity Descriptions. Ruobing Xie, Zhiyuan Liu, Jia Jia, Huanbo Luan, Maosong Sun. AAAI 2016.
26.ProPPR: Learning First-Order Logic Embeddings via Matrix Factorization. William Yang Wang, William W. Cohen.IJCAI 2016.
27.SSP: Semantic Space Projection for Knowledge Graph Embedding with Text Descriptions. Han Xiao, Minlie Huang, Lian Meng, Xiaoyan Zhu. AAAI 2017.
28.ProjE: Embedding Projection for Knowledge Graph Completion. Baoxu Shi, Tim Weninger. AAAI 2017.
29.ANALOGY: Analogical Inference for Multi-relational Embeddings. Hanxiao Liu, Yuexin Wu, Yiming Yang. ICML 2017.
30.IKRL: Image-embodied Knowledge Representation Learning. Ruobing Xie, Zhiyuan Liu, Tat-Seng Chua, Huan-Bo Luan, Maosong Sun. IJCAI 2017.
31.ITransF: An Interpretable Knowledge Transfer Model for Knowledge Base Completion. Qizhe Xie, Xuezhe Ma, Zihang Dai, Eduard Hovy. ACL 2017.
32.RUGE: Knowledge Graph Embedding with Iterative Guidance from Soft Rules. Shu Guo, Quan Wang, Lihong Wang, Bin Wang, Li Guo. AAAI 2018.
33.ConMask: Open-World Knowledge Graph Completion. Baoxu Shi, Tim Weninger. AAAI 2018.
34.TorusE: Knowledge Graph Embedding on a Lie Group. Takuma Ebisu, Ryutaro Ichise. AAAI 2018.
35.On Multi-Relational Link Prediction with Bilinear Models. Yanjie Wang, Rainer Gemulla, Hui Li. AAAI 2018.
36.Convolutional 2D Knowledge Graph Embeddings. Tim Dettmers, Pasquale Minervini, Pontus Stenetorp, Sebastian Riedel. AAAI 2018.
37.Accurate Text-Enhanced Knowledge Graph Representation Learning. Bo An, Bo Chen, Xianpei Han, Le Sun.NAACL-HLT 2018.
38.KBGAN: Adversarial Learning for Knowledge Graph Embeddings. Liwei Cai, William Yang Wang. NAACL-HLT 2018.
39.ConvKB: A Novel Embedding Model for Knowledge Base Completion Based on Convolutional Neural Network.Dai Quoc Nguyen, Tu Dinh Nguyen, Dat Quoc Nguyen, Dinh Phung. NAACL-HLT 2018.
40.DSKG: A Deep Sequential Model for Knowledge Graph Completion. Lingbing Guo, Qingheng Zhang, Weiyi Ge,Wei Hu, Yuzhong Qu.CCKS 2018.
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