Mining maximal cliques from an uncertain graph

international conference on data engineering(2015)

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摘要
We consider mining dense substructures (maximal cliques) from an uncertain graph, which is a probability distribution on a set of deterministic graphs. For parameter 0 <; α <; 1, we consider the notion of an α-maximal clique in an uncertain graph. We present matching upper and lower bounds on the number of α-maximal cliques possible within a (uncertain) graph. We present an algorithm to enumerate α-maximal cliques whose worst-case runtime is near-optimal, and an experimental evaluation showing the practical utility of the algorithm.
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关键词
data mining,graph theory,probability,deterministic graphs,mining dense substructures,mining maximal cliques,probability distribution,uncertain graph,worst case runtime
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