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Hierarchical Community Evolution Mining from Dynamic Networks

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Web-Age Information Management (WAIM 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9098))

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Abstract

Research on community evolution contributes to understanding the nature of network evolution. Previous community evolution studies have two defects: (1) the algorithms do not have sufficient stability or cannot handle the radical structure change of communities, and (2) they cannot reveal the evolutionary regularities with multiple levels. To solve these problems, this paper proposes a new method for mining the evolution of communities from dynamic networks. Experiments demonstrate that compared with traditional methods, our work significantly improves the algorithm performances.

This paper is supported by NSFC No. 61103043, and 61173099. And Chuan Li is the associate author.

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Author information

Authors and Affiliations

  1. College of Computer Science, Sichuan University, Chengdu, 610065, China

    Yonghui Zhang, Chuan Li, Yanmei Li, Changjie Tang & Ning Yang

Authors
  1. Yonghui Zhang
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  2. Chuan Li
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  3. Yanmei Li
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  4. Changjie Tang
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  5. Ning Yang
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Corresponding author

Correspondence to Chuan Li .

Editor information

Editors and Affiliations

  1. Google, CA, USA

    Xin Luna Dong

  2. Postdoc Apartments (Hong Lou) 4-1-4, Shandong University, Li Cheng, Jinan, China

    Xiaohui Yu

  3. Tsinghua University, Beijing, China

    Jian Li

  4. Northeastern University, BOSTON, USA

    Yizhou Sun

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© 2015 Springer International Publishing Switzerland

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Zhang, Y., Li, C., Li, Y., Tang, C., Yang, N. (2015). Hierarchical Community Evolution Mining from Dynamic Networks. In: Dong, X., Yu, X., Li, J., Sun, Y. (eds) Web-Age Information Management. WAIM 2015. Lecture Notes in Computer Science(), vol 9098. Springer, Cham. https://doi.org/10.1007/978-3-319-21042-1_50

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  • DOI: https://doi.org/10.1007/978-3-319-21042-1_50

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-21041-4

  • Online ISBN: 978-3-319-21042-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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