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Bipartite graphs have been used to represent data relationships in many data-mining applications such as in E-commerce recommendation systems.
Amazon.com recommendations: item-to-item collaborative filtering
G. Linden, B. Smith, and J. York · 2003
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Collective Classification in Network Data
P. Sen, G. Namata, M. Bilgic, L. Getoor, B. Galligher, and T. Eliassi-Rad · 2008
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The Graph Neural Network Model
F. Scarselli, M. Gori, A. C. Tsoi, M. Hagenbuchner, and G. Monfardini · 2009
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Distributed representations of words and phrases and their compositionality
T. Mikolov, I. Sutskever, K. Chen, G. S. Corrado, and J. Dean · 2013
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Generative Adversarial Networks
I. J. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio · 2014
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DeepWalk: Online Learning of Social Representations
B. Perozzi, R. Al-Rfou, and S. Skiena · 2014
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Domain-adversarial training of neural networks
Y. Ganin, E. Ustinova, H. Ajakan, P. Germain, H. Larochelle, F. Laviolette, M. Marchand, and V. Lempitsky · 2015
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node2vec: Scalable Feature Learning for Networks
A. Grover and J. Leskovec · 2016
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Variational Graph Auto-Encoders
T. N. Kipf and M. Welling · 2016
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Structural Deep Network Embedding
D. Wang, P. Cui, and W. Zhu · 2016
Cited alongside, same era.
metapath2vec: Scalable representation learning for heterogeneous networks
Y. Dong, N. V. Chawla, and A. Swami · 2017
Cited alongside, same era.
Inductive Representation Learning on Large Graphs
W. L. Hamilton, R. Ying, and J. Leskovec · 2017
Cited alongside, same era.
Semi-supervised classification with graph convolutional networks
T. N. Kipf and M. Welling · 2017
Cited alongside, same era.
FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling
Adversarially Regularized Graph Autoencoder for Graph Embedding
S. Pan, R. Hu, G. Long, J. Jiang, L. Yao, and C. Zhang · 2018
Later among the works it cites.
DeepInf: Social Influence Prediction with Deep Learning
J. Qiu, J. Tang, H. Ma, Y. Dong, K. Wang, and J. Tang · 2018
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Representation Learning for Scene Graph Completion via Jointly Structural and Visual Embedding
H. Wan, Y. Luo, B. Peng, and W.-S. Zheng · 2018
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Graph R-CNN for Scene Graph Generation
J. Yang, J. Lu, S. Lee, D. Batra, and D. Parikh · 2018
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Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation
J. You, B. Liu, Z. Ying, V. Pande, and J. Leskovec · 2018
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J. Chen, T. Ma, and C. Xiao · 2018
Cited alongside, same era.
Adaptive sampling towards fast graph representation learning
W. Huang, T. Zhang, Y. Rong, and J. Huang · 2018
Cited alongside, same era.
Junction Tree Variational Autoencoder for Molecular Graph Generation
W. Jin, R. Barzilay, and T. Jaakkola · 2018
Cited alongside, same era.
Matrix factorization techniques for recommender systems
Y. Koren, R. Bell, and C. Volinsky
Cited in the paper.
Modeling relational data with graph convolutional networks
M. Schlichtkrull, T. N. Kipf, P. Bloem, R. v. d. Berg, I. Titov, and M. Welling
Cited in the paper.
PTE: Predictive text embedding through large-scale heterogeneous text networks
J. Tang, M. Qu, and Q. Mei
Cited in the paper.
W. Hu, B. Liu, J. Gomes, M. Zitnik, P. Liang, V. Pande, and J. Leskovec · 2019
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N-gram graph: Simple unsupervised representation for graphs, with applications to molecules
S. Liu, M. F. Demirel, and Y. Liang · 2019
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A comprehensive survey on graph neural networks
Z. Wu, S. Pan, F. Chen, G. Long, C. Zhang, and P. S. Yu · 2019
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