表示学习小组

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综述

  1. Representation Learning: A Review and New Perspectives. Yoshua Bengio, Aaron Courville, and Pascal Vincent. TPAMI 2013. paper
  2. 知识表示学习研究进展. 刘知远,孙茂松,林衍凯,谢若冰. 计算机研究与发展 2016. paper
  3. A Review of Relational Machine Learning for Knowledge Graphs. Maximilian Nickel, Kevin Murphy, Volker Tresp, Evgeniy Gabrilovich. Proceedings of the IEEE 2016. paper
  4. Knowledge Graph Embedding: A Survey of Approaches and Applications. Quan Wang, Zhendong Mao, Bin Wang, Li Guo. TKDE 2017. paper
  5. A Survey on Heterogeneous Graph Embedding: Methods, Techniques, Applications and Sources. Xiao Wang, Deyu Bo, Chuan Shi, Shaohua Fan, Yanfang Ye,Philip S. Yu. IEEE Transactions on Big Data. paper

基于翻译模型

  1. TransE: Translating Embeddings for Modeling Multi-relational Data. Antoine Bordes, Nicolas Usunier, Alberto Garcia-Duran, Jason Weston, Oksana Yakhnenko. NIPS 2013. paper
  2. TransH: Knowledge Graph Embedding by Translating on Hyperplanes. Zhen Wang, Jianwen Zhang, Jianlin Feng, Zheng Chen. AAAI 2014. paper
  3. TransR & CTransR: Learning Entity and Relation Embeddings for Knowledge Graph Completion. Yankai Lin, Zhiyuan Liu, Maosong Sun, Yang Liu, Xuan Zhu. AAAI 2015. paper
  4. TransD: Knowledge Graph Embedding via Dynamic Mapping Matrix. Guoliang Ji, Shizhu He, Liheng Xu, Kang Liu, Jun Zhao. ACL 2015. paper
  5. TransA: An Adaptive Approach for Knowledge Graph Embedding. Han Xiao, Minlie Huang, Hao Yu, Xiaoyan Zhu. arXiv 2015. paper
  6. TranSparse: Knowledge Graph Completion with Adaptive Sparse Transfer Matrix. Guoliang Ji, Kang Liu, Shizhu He, Jun Zhao. AAAI 2016. paper
  7. TransG: A Generative Mixture Model for Knowledge Graph Embedding. Han Xiao, Minlie Huang, Xiaoyan Zhu. ACL 2016 paper
  8. KG2E: Learning to Represent Knowledge Graphs with Gaussian Embedding. Shizhu He, Kang Liu, Guoliang Ji and Jun Zhao. CIKM 2015. paper

融入关系路径

  1. 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
  2. Traversing Knowledge Graphs in Vector Space. Kelvin Guu, John Miller, Percy Liang. EMNLP 2015. paper
  3. Knowledge Graph Embedding with Hierarchical Relation Structure. Zhao Zhang, Fuzhen Zhuang, Meng Qu, Fen Lin, Qing He. ACL 2018. paper
  4. TransRHS: A Representation Learning Method for Knowledge Graphs with Relation Hierarchical Structure. Fuxiang Zhang, Xin Wang, Zhao Li, Jianxin Li. IJCAI 2020. paper

实体类型方向

  1. Type-Constrained Representation Learning in Knowledge Graphs. Denis Krompa, Stephan Baier, Volker Tresp. The Semantic Web - ISWC 2015. paper
  2. TKRL: Representation Learning of Knowledge Graphs with Hierarchical Types. Ruobing Xie, Zhiyuan Liu, Maosong Sun. IJCAI 2016. paper code
  3. KR-EAR: Knowledge Representation Learning with Entities, Attributes and Relations. Yankai Lin, Zhiyuan Liu, Maosong Sun. IJCAI 2016. paper code
  4. Differentiating Concepts and Instances for Knowledge Graph Embedding. Xin Lv, Lei Hou, Juanzi Li, Zhiyuan Liu. EMNLP 2018. paper code
  5. AutoETER: Automated Entity Type Representation for Knowledge Graph Embedding. Guanglin Niu, Bo Li, Yongfei Zhang, Shiliang Pu, Jingyang Li. EMNLP 2020. paper