Abstract

Given a simple undirected graph GG, the maximum kk-club problem is to find a maximum-cardinality subset of nodes inducing a subgraph of diameter at most kk in GG. This NP-hard generalization of clique, originally introduced to model low diameter clusters in social networks, is of interest in network-based data mining and clustering applications. We give two MAX-SAT formulations of the problem and show that two exact methods resulting from our encodings outperform significantly the state-of-the-art exact methods when evaluated both on sparse and dense random graphs as well as on diverse real-life graphs from the literature.

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