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Latent Feature Representation for Cohesive Community Detection Based on Convolutional Auto-Encoder

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Big Data (BigData 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1120))

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Abstract

It is important to identify community structures for characterizing and understanding complex systems. Community detection models, like stochastic models and modularity maximization models, lack of the ability of nonlinear mapping, which leads to unsatisfactory performance when detecting communities of complex real-world networks. To address this issue, we propose a nonlinear method based on Convolutional Auto-Encoder (ConvAE) to improve the cohesiveness of community detection. We combine the convolution neural network and auto-encoder to improve the ability of nonlinear mapping of the proposed model. Moreover, to better characterize relations between nodes, we redefine the similarity between nodes for preprocessing the input data. We conduct extensive experiments on both the synthetic networks and real-world networks, and the results demonstrate the effectiveness of the proposed method and the superior performance over traditional methods and other deep learning based methods.

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Acknowledgments

This work is supported by the Natural Science Foundation of China (No. 61672276), Natural Science Foundation of Jiangsu Province of China (No. BK20161406).

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Authors and Affiliations

  1. State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, 210023, China

    Chun Li, Wenfeng Shi & Lin Shang

Authors
  1. Chun Li
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  2. Wenfeng Shi
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  3. Lin Shang
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Corresponding author

Correspondence to Lin Shang .

Editor information

Editors and Affiliations

  1. Huazhong University of Science and Technology, Wuhan, China

    Hai Jin

  2. East China Normal University, Shanghai, China

    Xuemin Lin

  3. Chinese Academy of Sciences, Beijing, China

    Xueqi Cheng

  4. Huazhong University of Science and Technology, Wuhan, China

    Xuanhua Shi

  5. National University of Defense Technology, Changsha, China

    Nong Xiao

  6. Nanjing University, Nanjing, China

    Yihua Huang

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Li, C., Shi, W., Shang, L. (2019). Latent Feature Representation for Cohesive Community Detection Based on Convolutional Auto-Encoder. In: Jin, H., Lin, X., Cheng, X., Shi, X., Xiao, N., Huang, Y. (eds) Big Data. BigData 2019. Communications in Computer and Information Science, vol 1120. Springer, Singapore. https://doi.org/10.1007/978-981-15-1899-7_27

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  • DOI: https://doi.org/10.1007/978-981-15-1899-7_27

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-1898-0

  • Online ISBN: 978-981-15-1899-7

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