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As communities represent similar opinions, similar functions, similar purposes, etc., community detection is an important and extremely useful tool in both scientific inquiry and data analytics.
On spectral clustering: analysis and an algorithm
A. Ng, M. Jordan, and Y. Weiss · 2002
Earlier work this paper cites.
Detecting functional modules in the yeast protein-protein interaction network
J. Chen and B. Yuan · 2006
Earlier work this paper cites.
Maps of random walks on complex networks reveal community structure
M. Rosvall and C. Bergstrom · 2008
Earlier work this paper cites.
Community structure of the physical review citation network
P. Chen and S. Redner · 2010
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Community detection in graphs
S. Fortunato · 2010
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Stochastic blockmodels and community structure in networks
B. Karrer and M. Newman · 2011
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Sparse filtering
J. Ngiam, Z. Chen, S. Bhaskar, P. Koh, and A. Ng · 2011
Earlier work this paper cites.
Community detection in networks with node attributes
J. Yang, J. McAuley, and J. Leskovec · 2013
Earlier work this paper cites.
Learning deep representations for graph clustering
F. Tian, B. Gao, Q. Cui, E. Chen, and T. Liu · 2014
Earlier work this paper cites.
Heterogeneous network embedding via deep architectures
S. Chang, W. Han, J. Tang, G. Qi, C. Aggarwal, and T. Huang · 2015
Earlier work this paper cites.
Deep learning
Y. LeCun, Y. Bengio, and G. Hinton · 2015
Earlier work this paper cites.
Community detection in networks: A user guide
S. Fortunato and D. Hric · 2016
Earlier work this paper cites.
Modularity based community detection with deep learning
L. Yang, X. Cao, D. He, C. Wang, X. Wang, and W. Zhang · 2016
Earlier work this paper cites.
Learning community embedding with community detection and node embedding on graphs
S. Cavallari, V. Zheng, H. Cai, K. Chang, and E. Cambria · 2017
Earlier work this paper cites.
Hin2vec: Explore meta-paths in heterogeneous information networks for representation learning
T. Fu, W. Lee, and Z. Lei · 2017
Earlier work this paper cites.
Joint identification of network communities and semantics via integrative modeling of network topologies and node contents
D. He, Z. Feng, D. Jin, X. Wang, and W. Zhang · 2017
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Deep community detection in topologically incomplete networks
X. Xin, C. Wang, X. Ying, and B. Wang · 2017
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Enterprise community detection
J. Zhang, P. S. Yu, and Y. Lv · 2017
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DFuzzy: A deep learning-based fuzzy clustering model for large graphs
V. Bhatia and R. Rani · 2018
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Autoencoder based community detection with adaptive integration of network topology and node contents
J. Cao, D. Jin, and J. Dang · 2018
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Incorporating network structure with node contents for community detection on large networks using deep learning
A distributed overlapping community detection model for large graphs using autoencoder
V. Bhatia and R. Rani · 2019
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Supervised community detection with line graph neural networks
Z. Chen, L. Li, and J. Bruna · 2019
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Sparse network embedding for community detection and sign prediction in signed social networks
B. Hu, H. Wang, X. Yu, W. Yuan, and T. He · 2019
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CommunityGAN: Community detection with generative adversarial nets
Y. Jia, Q. Zhang, W. Zhang, and X. Wang · 2019
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Graph convolutional networks meet markov random fields: Semi-supervised community detection in attribute networks
D. Jin, Z. Liu, W. Li, D. He, and W. Zhang · 2019
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Overlapping community detection with graph neural networks
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J. Cao, D. Jin, L. Yang, and J. Dang · 2018
Cited alongside, same era.
Learning community structure with variational autoencoder
J. Choong, X. Liu, and T. Murata · 2018
Cited alongside, same era.
Community detection in attributed graphs: an embedding approach
Y. Li, C. Sha, X. Huang, and Y. Zhang · 2018
Cited alongside, same era.
Deep network embedding for graph representation learning in signed networks
X. Shen and F. Chung · 2018
Cited alongside, same era.
Improved deep embeddings for inferencing with multi-layered networks
H. Song and J. Thiagarajan · 2018
Cited alongside, same era.
Community discovery in networks with deep sparse filtering
Y. Xie, M. Gong, S. Wang, and B. Yu · 2018
Cited alongside, same era.
Deep autoencoder-like nonnegative matrix factorization for community detection
F. Ye, C. Chen, and Z. Zheng · 2018
Cited alongside, same era.
O. Shchur and S. Gunnemann · 2019
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A deep learning based community detection approach
G. Sperlí · 2019
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vGraph: A generative model for joint community detection and node representation learning
F. Sun, M. Qu, J. Hoffmann, C. Huang, and J. Tang · 2019
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A unified framework for community detection and network representation learning
C. Tu, X. Zeng, H. Wang, Z. Zhang, Z. Liu, M. Sun, B. Zhang, and L. Lin · 2019
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Learning graph representation with generative adversarial nets
H. Wang, J. Wang, J. Wang, M. Zhao, W. Zhang, F. Zhang, W. Li, X. Xie, and M. Guo · 2019
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Link prediction with signed latent factors in signed social networks
P. Xu, W. Hu, J. Wu, and B. Du · 2019
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Cross-domain network representations
S. Xue, J. Lu, and G. Zhang · 2019
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Detecting the evolving community structure in dynamic social networks
F. Liu, J. Wu, S. Xue, C. Zhou, J. Yang, and Q. Sheng · 2020
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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 · 2020
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