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Complex networks are intrinsically present in a wide range of applications. Real world networks have several unique properties, such as, sparsity, node degree distribution, which follow a power law and a large amount of triangles that further form larger cliques. Triangles and cluster coefficient, which are usually used to find groups, are not always enough to distinguish a different node neighborhood topology. By using cliques of sizes 4 and 5, it is possible to study how triangles become involved to form large cliques.
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