K-connected cores computation in large dual networks

Publication Type:
Conference Proceeding
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2018, 10827 LNCS pp. 169 - 186
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© Springer International Publishing AG, part of Springer Nature 2018. Computing k-cores 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-core in dual graphs, we formulate a k-connected core (k-CCO) model in dual graphs. A k-CCO is a k-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-CCOs. We also propose three algorithms for computing all maximum-connected cores (MCCO), which are the existing k-CCOs 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.
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