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A Community Detection Algorithm Based on the Similarity Sequence

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Web Information Systems Engineering – WISE 2014 (WISE 2014)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8786))

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Abstract

Community detection is a hot topic in the field of complex social networks. It is of great value to personalized recommendation, protein structure analysis, public opinion analysis, etc. However, most existing algorithms detect communities with misclassified nodes and peripheries, and the clustering accuracy is not high. In this paper, in terms of the agglomerative hierarchical clustering, a community detection algorithm based on the similarity sequence is proposed, named as ACSS (Agglomerative Clustering Algorithm based on the Similarity Sequence). First, similarities of nodes are sorted in descending order to get a sequence. Then pairs of nodes are merged according to the sequence to construct a preliminary community structure. Secondly, the agglomerative clustering process is carried out to get the optimal community structure. The proposed algorithm is tested on real network and computer-generated network data sets. Experimental results show that ACSS can solve the problem of neglecting peripheries. Compared with the existing representative algorithms, it can detect stronger community structure, and improve the clustering accuracy.

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Author information

Authors and Affiliations

  1. School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, PR China

    Hongwei Lu, Qian Zhao & Zaobin Gan

Authors
  1. Hongwei Lu
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  2. Qian Zhao
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  3. Zaobin Gan
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Editor information

Editors and Affiliations

  1. University of New South Wales, Sydney, Australia

    Boualem Benatallah

  2. Boston University, Boston, MA, USA

    Azer Bestavros

  3. Aristotle University of Thessaloniki, Thessaloniki, Greece

    Yannis Manolopoulos  & Athena Vakali  & 

  4. Victoria University, Footscray, VIC, Australia

    Yanchun Zhang

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© 2014 Springer International Publishing Switzerland

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Lu, H., Zhao, Q., Gan, Z. (2014). A Community Detection Algorithm Based on the Similarity Sequence. In: Benatallah, B., Bestavros, A., Manolopoulos, Y., Vakali, A., Zhang, Y. (eds) Web Information Systems Engineering – WISE 2014. WISE 2014. Lecture Notes in Computer Science, vol 8786. Springer, Cham. https://doi.org/10.1007/978-3-319-11749-2_5

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  • DOI: https://doi.org/10.1007/978-3-319-11749-2_5

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11748-5

  • Online ISBN: 978-3-319-11749-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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