K-Connected Cores Computation in Large Dual Networks

  • Lingxi Yue
  • Dong Wen
  • Lizhen Cui
  • Lu Qin
  • Yongqing Zheng
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10827)


Computing \(k\text {-}core\)s is a fundamental and important graph problem, which can be applied in many areas, such as community detection, network visualization, and network topology analysis. Due to the complex relationship between different entities, dual graph widely exists in the applications. A dual graph contains a physical graph and a conceptual graph, both of which have the same vertex set. Given that there exist no previous studies on the \(k\text {-}core\) in dual graphs, we formulate a k-connected core (\(k\text {-}CCO\)) model in dual graphs. A \(k\text {-}CCO\) is a \(k\text {-}core\) in the conceptual graph, and also connected in the physical graph. Given a dual graph and an integer k, we propose a polynomial time algorithm for computing all \(k\text {-}CCO\)s. We also propose three algorithms for computing all maximum-connected cores (\(MCCO\)), which are the existing \(k\text {-}CCO\)s such that a \((k+1)\)-\(CCO\) does not exist. We conduct extensive experiments on six real-world datasets and several synthetic datasets. The experimental results demonstrate the effectiveness and efficiency of our proposed algorithms.



The work is supported by the National Key R&D Program (No. 2017YFB1400102, No. 2016YFB1000602), NSFC (No. 61572295), and SDNSF (No. ZR2017ZB0420).


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Lingxi Yue
    • 1
  • Dong Wen
    • 2
  • Lizhen Cui
    • 1
  • Lu Qin
    • 2
  • Yongqing Zheng
    • 1
  1. 1.School of Software EngineeringShandong UniversityJinanChina
  2. 2.Centre for Artificial IntelligenceUniversity of Technology SydneyUltimoAustralia

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