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Analyzing Community Structure Based on Topology Potential over Complex Network System

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Geo-Spatial Knowledge and Intelligence (GSKI 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 849))

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Abstract

Community structure is one of complex network properties which reveals the main organizing proposition in most real-world complex networks. The special interests are groups of vertices within the intense edges or connections that are not only overlapping, but also change over-time. In this paper, we present the overview of structured complex network properties that affect the process of discovering community structure. Topology potential of nodes in complex network is also described. Topology potential is a measurement method to investigate the interaction among community members. From the recent literatures, the community structure discovered by topology potential needs to be improved in term of performance and accuracy in order to obtain more meaningful results.

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Acknowledgments

This work was supported by National Key Research and Development Plan of China (2016YFB0502604, 2016YFC0803000), National Natural Science Fund of China (61472039), and Frontier and Interdisciplinary Innovation Program of Beijing Institute of Technology (2016CX11006), International Scientific and Technological Cooperation and Academic Exchange Program of Beijing Institute of Technology (GZ2016085103).

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Authors and Affiliations

  1. School of Software Engineering, Beijing Institute of Technology, No. 5, South Zhong Guan Cun Street, Beijing, 100081, People’s Republic of China

    Kanokwan Malang, Shuliang Wang & Tianru Dai

Authors
  1. Kanokwan Malang
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  2. Shuliang Wang
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  3. Tianru Dai
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Corresponding author

Correspondence to Kanokwan Malang .

Editor information

Editors and Affiliations

  1. Beijing Institute of Technology, Beijing, China

    Hanning Yuan

  2. Beijing Institute of Technology, Beijing, China

    Jing Geng

  3. Beijing Institute of Technology, Beijing, China

    Chuanlu Liu

  4. Wuhan University, Wuhan, China

    Fuling Bian

  5. Beijing Institute of Technology, Beijing, China

    Tisinee Surapunt

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Malang, K., Wang, S., Dai, T. (2018). Analyzing Community Structure Based on Topology Potential over Complex Network System. In: Yuan, H., Geng, J., Liu, C., Bian, F., Surapunt, T. (eds) Geo-Spatial Knowledge and Intelligence. GSKI 2017. Communications in Computer and Information Science, vol 849. Springer, Singapore. https://doi.org/10.1007/978-981-13-0896-3_6

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  • DOI: https://doi.org/10.1007/978-981-13-0896-3_6

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-0895-6

  • Online ISBN: 978-981-13-0896-3

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