/NRLPapers

Must-read papers on network representation learning (NRL) / network embedding (NE)

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Must-read papers on NRL/NE.

NRL: network representation learning. NE: network embedding.

Contributed by Cunchao Tu, Yuan Yao and Zhengyan Zhang.

We release OpenNE, an open source toolkit for NE/NRL. This repository provides a standard NE/NRL(Network Representation Learning）training and testing framework. Currently, the implemented models in OpenNE include DeepWalk, LINE, node2vec, GraRep, TADW and GCN.

Survey papers:

  1. Representation Learning on Graphs: Methods and Applications. William L. Hamilton, Rex Ying, Jure Leskovec 2017. paper

  2. Graph Embedding Techniques, Applications, and Performance: A Survey. Palash Goyal, Emilio Ferrara 2017. paper

  3. A Comprehensive Survey of Graph Embedding: Problems, Techniques and Applications. Hongyun Cai, Vincent W. Zheng, Kevin Chen-Chuan Chang 2017. paper

  4. Network Representation Learning: A Survey. Daokun Zhang, Jie Yin, Xingquan Zhu, Chengqi Zhang 2018. paper

  5. Network Representation Learning: An Overview.(In Chinese) Cunchao Tu, Cheng Yang, Zhiyuan Liu, Maosong Sun 2017. paper

Journal and Conference papers:

  1. DeepWalk: Online Learning of Social Representations. Bryan Perozzi, Rami Al-Rfou, Steven Skiena. KDD 2014. paper code

  2. Learning Latent Representations of Nodes for Classifying in Heterogeneous Social Networks. Yann Jacob, Ludovic Denoyer, Patrick Gallinar. WSDM 2014. paper

  3. Non-transitive Hashing with Latent Similarity Componets. Mingdong Ou, Peng Cui, Fei Wang, Jun Wang, Wenwu Zhu. KDD 2015. paper

  4. GraRep: Learning Graph Representations with Global Structural Information. Shaosheng Cao, Wei Lu, Qiongkai Xu. CIKM 2015. paper code

  5. LINE: Large-scale Information Network Embedding. Jian Tang, Meng Qu, Mingzhe Wang, Ming Zhang, Jun Yan, Qiaozhu Me. WWW 2015. paper code

  6. Network Representation Learning with Rich Text Information. Cheng Yang, Zhiyuan Liu, Deli Zhao, Maosong Sun, Edward Y. Chang. IJCAI 2015. paper code

  7. PTE: Predictive Text Embedding through Large-scale Heterogeneous Text Networks. Jian Tang, Meng Qu, Qiaozhu Mei. KDD 2015. paper code

  8. Heterogeneous Network Embedding via Deep Architectures. Shiyu Chang, Wei Han, Jiliang Tang, Guo-Jun Qi, Charu C. Aggarwal, Thomas S. Huang. KDD 2015. paper

  9. Deep Neural Networks for Learning Graph Representations. Shaosheng Cao, Wei Lu, Xiongkai Xu. AAAI 2016. paper code

  10. Asymmetric Transitivity Preserving Graph Embedding. Mingdong Ou, Peng Cui, Jian Pei, Ziwei Zhang, Wenwu Zhu. KDD 2016. paper

  11. Revisiting Semi-supervised Learning with Graph Embeddings. Zhilin Yang, William W. Cohen, Ruslan Salakhutdinov. ICML 2016. paper

  12. node2vec: Scalable Feature Learning for Networks. Aditya Grover, Jure Leskovec. KDD 2016. paper code

  13. Max-Margin DeepWalk: Discriminative Learning of Network Representation. Cunchao Tu, Weicheng Zhang, Zhiyuan Liu, Maosong Sun. IJCAI 2016. paper code

  14. Tri-Party Deep Network Representation. Shirui Pan, Jia Wu, Xingquan Zhu, Chengqi Zhang, Yang Wang. IJCAI 2016. paper

  15. Discriminative Deep RandomWalk for Network Classification. Juzheng Li, Jun Zhu, Bo Zhang. ACL 2016. paper

  16. Structural Deep Network Embedding. Daixin Wang, Peng Cui, Wenwu Zhu. KDD 2016. paper

  17. Structural Neighborhood Based Classification of Nodes in a Network. Sharad Nandanwar, M. N. Murty. KDD 2016. paper

  18. Community Preserving Network Embedding. Xiao Wang, Peng Cui, Jing Wang, Jian Pei, Wenwu Zhu, Shiqiang Yang. AAAI 2017. paper

  19. Semi-supervised Classification with Graph Convolutional Networks. Thomas N. Kipf, Max Welling. ICLR 2017. paper code

  20. CANE: Context-Aware Network Embedding for Relation Modeling. Cunchao Tu, Han Liu, Zhiyuan Liu, Maosong Sun. ACL 2017. paper code

  21. Fast Network Embedding Enhancement via High Order Proximity Approximation. Cheng Yang, Maosong Sun, Zhiyuan Liu, Cunchao Tu. IJCAI 2017. paper code

  22. TransNet: Translation-Based Network Representation Learning for Social Relation Extraction. Cunchao Tu, Zhengyan Zhang, Zhiyuan Liu, Maosong Sun. IJCAI 2017. paper code

  23. metapath2vec: Scalable Representation Learning for Heterogeneous Networks. Yuxiao Dong, Nitesh V. Chawla, Ananthram Swami. KDD 2017. paper code

  24. Learning from Labeled and Unlabeled Vertices in Networks. Wei Ye, Linfei Zhou, Dominik Mautz, Claudia Plant, Christian Böhm. KDD 2017. paper

  25. Unsupervised Feature Selection in Signed Social Networks. Kewei Cheng, Jundong Li, Huan Liu. KDD 2017. paper

  26. struc2vec: Learning Node Representations from Structural Identity. Leonardo F. R. Ribeiro, Pedro H. P. Saverese, Daniel R. Figueiredo. KDD 2017. paper code

  27. Label Informed Attributed Network Embedding. Xiao Huang, Jundong Li, Xia Hu. WSDM 2017. paper code

  28. Accelerated Attributed Network Embedding. Xiao Huang, Jundong Li, Xia Hu. SDM 2017. paper code

  29. Inductive Representation Learning on Large Graphs. William L. Hamilton, Rex Ying, Jure Leskovec. NIPS 2017. paper code

  30. Variation Autoencoder Based Network Representation Learning for Classification. Hang Li, Haozheng Wang, Zhenglu Yang, Masato Odagaki. ACL 2017. paper

  31. Preserving Proximity and Global Ranking for Node Embedding. Yi-An Lai, Chin-Chi Hsu, Wenhao Chen, Mi-Yen Yeh, Shou-De Lin. NIPS 2017.

  32. Learning Graph Embeddings with Embedding Propagation. Alberto Garcia Duran, Mathias Niepert. NIPS 2017. paper

  33. Name Disambiguation in Anonymized Graphs using Network Embedding. Baichuan Zhang, Mohammad Al Hasan. CIKM 2017. paper

  34. Enhancing the Network Embedding Quality with Structural Similarity. Tianshu Lyu, Yuan Zhang, Yan Zhang. CIKM 2017. paper

  35. Attributed Signed Network Embedding. Suhang Wang, Charu Aggarwal, Jiliang Tang, Huan Liu. CIKM 2017. paper

  36. Attributed Network Embedding for Learning in a Dynamic Environment. Jundong Li, Harsh Dani, Xia Hu, Jiliang Tang, Yi Chang, Huan Liu. CIKM 2017. paper

  37. HIN2Vec: Explore Meta-paths in Heterogeneous Information Networks for Representation Learning. Tao-yang Fu, Wang-Chien Lee, Zhen Lei. CIKM 2017. paper

  38. From Properties to Links: Deep Network Embedding on Incomplete Graphs. Dejian Yang, Senzhang Wang, Chaozhuo Li, Xiaoming Zhang, Zhoujun Li. CIKM 2017. paper

  39. An Attention-based Collaboration Framework for Multi-View Network Representation Learning. Meng Qu, Jian Tang, Jingbo Shang, Xiang Ren, Ming Zhang, Jiawei Han. CIKM 2017. paper

  40. On Embedding Uncertain Graphs. Jiafeng Hu, Reynold Cheng, Zhipeng Huang, Yixang Fang, Siqiang Luo. CIKM 2017. paper

  41. Multi-view Clustering with Graph Embedding for Connectome Analysis. Guixiang Ma, Lifang He, Chun-Ta Lu, Weixiang Shao, Philip S Yu, Alex D Leow, Ann B Ragin. CIKM 2017. paper

  42. Learning Node Embeddings in Interaction Graphs. Yao Zhang, Yun Xiong, Xiangnan Kong, Yangyong Zhu. CIKM 2017. paper

  43. Learning Community Embedding with Community Detection and Node Embedding on Graphs. Sandro Cavallari, Vincent W. Zheng, Hongyun Cai, Kevin ChenChuan Chang, Erik Cambria. CIKM 2017. paper code

  44. Network Embedding as Matrix Factorization: Unifying DeepWalk, LINE, PTE, and node2vec. Jiezhong Qiu, Yuxiao Dong, Hao Ma, Jian Li, Kuansan Wang, Jie Tang. WSDM 2018. paper

  45. Exploring Expert Cognition for Attributed Network Embedding. Xiao Huang, Qingquan Song, Jundong Li, Xia Ben Hu. WSDM 2018. paper

  46. SHINE: Signed Heterogeneous Information Network Embedding for Sentiment Link Prediction. Hongwei Wang, Fuzheng Zhang, Min Hou, Xing Xie, Minyi Guo, Qi Liu. WSDM 2018. paper

  47. Multidimensional Network Embedding with Hierarchical Structures. Yao Ma, Zhaochun Ren, Ziheng Jiang, Jiliang Tang, Dawei Yin. WSDM 2018. paper

  48. Curriculum Learning for Heterogeneous Star Network Embedding via Deep Reinforcement Learning. Meng Qu, Jian Tang, Jiawei Han. WSDM 2018. paper

  49. Adversarial Network Embedding. Quanyu Dai, Qiang Li, Jian Tang, Dan Wang. AAAI 2018. paper

  50. COSINE: Community-Preserving Social Network Embedding from Information Diffusion Cascades. Yuan Zhang, Tianshu Lyu, Yan Zhang. AAAI 2018.

  51. Dynamic Network Embedding by Modeling Triadic Closure Process. Lekui Zhou, Yang Yang, Xiang Ren, Fei Wu, Yueting Zhuang. AAAI 2018. paper

  52. Multi-facet Network Embedding: Beyond the General Solution of Detection and Representation. Liang Yang, Xiaochun Cao, Yuanfang Guo. AAAI 2018.

  53. RSDNE: Exploring Relaxed Similarity and Dissimilarity from Completely-imbalanced Labels for Network Embedding. Zheng Wang, Xiaojun Ye, Chaokun Wang, YueXin Wu, Changping Wang, Kaiwen Liang. AAAI 2018. paper code

  54. Link Prediction via Subgraph Embedding-Based Convex Matrix Completion. Zhu Cao, Linlin Wang, Gerard De melo. AAAI 2018.

  55. Generative Adversarial Network based Heterogeneous Bibliographic Network Representation for Personalized Citation Recommendation. J. Han, Xiaoyan Cai, Libin Yang. AAAI 2018.

  56. DepthLGP: Learning Embeddings of Out-of-Sample Nodes in Dynamic Networks. Jianxin Ma, Peng Cui, Wenwu Zhu. AAAI 2018. paper

  57. Structural Deep Embedding for Hyper-Networks. Ke Tu, Peng Cui, Xiao Wang, fei Wang, Wenwu Zhu. AAAI 2018. paper

  58. TIMERS: Error-Bounded SVD Restart on Dynamic Networks. Ziwei Zhang, Peng Cui, Jian Pei, Xiao Wang, Wenwu Zhu. AAAI 2018. paper

  59. Community Detection in Attributed Graphs: An Embedding Approach. Ye Li, Chaofeng Sha, Xin Huang, Yanchun Zhang. AAAI 2018.

  60. Bernoulli Embeddings for Graphs. Vinith Misra, Sumit Bhatia. AAAI 2018. paper

  61. Distance-aware DAG Embedding for Proximity Search on Heterogeneous Graphs. Zemin Liu, Vincent W. Zheng, Zhou Zhao, Fanwei Zhu, Kevin Chen-Chuan Chang, Minghui Wu, Jing Ying. AAAI 2018.

  62. GraphGAN: Graph Representation Learning with Generative Adversarial Nets. Hongwei Wang, jia Wang, jialin Wang, MIAO ZHAO, Weinan Zhang, Fuzheng Zhang, Xie Xing, Minyi Guo. AAAI 2018. paper

  63. HARP: Hierarchical Representation Learning for Networks. Haochen Chen, Bryan Perozzi, Yifan Hu, Steven Skiena. AAAI 2018. paper code

  64. Representation Learning for Scale-free Networks. Rui Feng, Yang Yang, Wenjie Hu, Fei Wu, Yueting Zhuang. AAAI 2018. paper

  65. Social Rank Regulated Large-scale Network Embedding. Yupeng Gu, Yizhou Sun, Yanen Li, Yang Yang. WWW 2018. paper

  66. Co-Regularized Deep Multi-Network Embedding. Jingchao Ni, Shiyu Chang, Xiao Liu, Wei Cheng, Haifeng Chen, Dongkuan Xu, Xiang Zhang. WWW 2018.

  67. On Exploring Semantic Meanings of Links for Embedding Social Networks. Linchuan Xu, Xiaokai Wei, Jiannong Cao, Philip S Yu. WWW 2018. paper

  68. SIDE: Representation Learning in Signed Directed Networks. Junghwan Kim, Haekyu Park, Ji-Eun Lee, U Kang. WWW 2018. paper

Preprints

This section contains promising recent preprints.

  1. NetGAN: Generating Graphs via Random Walks Aleksandar Bojchevski, Oleksandr Shchur, Daniel Zügner, Stephan Günnemann. paper