Abstract
In social network analysis, a k-clique is a relaxed clique, i.e., a k-clique is a quasi-complete sub-graph. A k-clique in a graph is a sub-graph where the distance between any two vertices is no greater than k. The visualization of a small number of vertices can be easily performed in a graph. However, when the number of vertices and edges increases the visualization becomes incomprehensible. In this paper, we propose a new graph mining approach based on k-cliques. The concept of relaxed clique is extended to the whole graph, to achieve a general view, by covering the network with k-cliques. The sequence of k-clique covers is presented, combining small world concepts with community structure components. Computational results and examples are presented.
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Cavique, L., Mendes, A.B., Santos, J.M.A. (2009). An Algorithm to Discover the k-Clique Cover in Networks. In: Lopes, L.S., Lau, N., Mariano, P., Rocha, L.M. (eds) Progress in Artificial Intelligence. EPIA 2009. Lecture Notes in Computer Science(), vol 5816. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04686-5_30
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DOI: https://doi.org/10.1007/978-3-642-04686-5_30
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04685-8
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