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Erschienen in:
2018 | OriginalPaper | Buchkapitel
K-Connected Cores Computation in Large Dual Networks
verfasst von : Lingxi Yue, Dong Wen, Lizhen Cui, Lu Qin, Yongqing Zheng
Erschienen in: Database Systems for Advanced Applications
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Abstract
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.