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A Hybrid Spectral Method for Network Community Detection

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Web and Big Data (APWeb-WAIM 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10987))

Abstract

Community detection has been paid much attention, and a large number of community-detection methods have been proposed in the last decade. Spectral methods are widely used in many applications due to their solid mathematical foundations. In this paper, we propose a hybrid spectral method to effectively identify communities from networks. This method begins with a network-sparsification operation, which is expected to remove some between-community edges from the network to make the community boundaries clearer and sharper, then it utilizes an iterative spectral bisection algorithm to partition the network into small communities, and finally some of the small communities are merged to obtain the resulting community structure. We conducted extensive experiments on five real-world networks and two artificial networks, the experimental results show that our proposed method can extract high-quality community structures from networks effectively.

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Acknowledgements

This work was partially supported by the Fundamental Research Funds for the Central Universities, China (grant ID: lzujbky-2017-sp24, lzujbky-2017-192), program of Hui-Chun Chin and Tsung-Dao Lee Chinese Undergraduate Research Endowment, CURE (grant ID: LZU-JZH1923), and the Young Scientists Fund of the National Natural Science Foundation of China (grant ID: 61602225).

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Authors and Affiliations

  1. School of Information Science and Engineering, Lanzhou University, Lanzhou, 730000, China

    Jianjun Cheng, Longjie Li, Qi Li & Xiaoyun Chen

  2. Gansu Resources and Environmental Science Data Engineering Technology Research Center, Lanzhou, 730000, China

    Jianjun Cheng

  3. Department of Electronic Information Engineering, Lanzhou Vocational Technical College, Lanzhou, 730070, China

    Haijuan Yang

Authors
  1. Jianjun Cheng
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  2. Longjie Li
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  3. Haijuan Yang
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  4. Qi Li
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  5. Xiaoyun Chen
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Corresponding author

Correspondence to Xiaoyun Chen .

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Editors and Affiliations

  1. South China University of Technology, Guangzhou, China

    Yi Cai

  2. Nagoya University, Nagoya, Japan

    Yoshiharu Ishikawa

  3. Hong Kong Baptist University, Kowloon Tong, Hong Kong, China

    Jianliang Xu

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Cheng, J., Li, L., Yang, H., Li, Q., Chen, X. (2018). A Hybrid Spectral Method for Network Community Detection. In: Cai, Y., Ishikawa, Y., Xu, J. (eds) Web and Big Data. APWeb-WAIM 2018. Lecture Notes in Computer Science(), vol 10987. Springer, Cham. https://doi.org/10.1007/978-3-319-96890-2_8

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  • DOI: https://doi.org/10.1007/978-3-319-96890-2_8

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  • Print ISBN: 978-3-319-96889-6

  • Online ISBN: 978-3-319-96890-2

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