Abstract
In this paper, we consider the problem of enumerating all maximal cliques in a complex network G = (V, E) with n vertices and m edges. We propose an algorithm for enumerating all maximal cliques based on researches of the complex network properties. A novel branch and bound strategy by considering the clustering coefficient of a vertex is proposed. Our algorithm runs with time O (d^2*N*S) delay and in O (n + m) space. It requires O (n*D^2) time as a preprocessing, where D, N, S, d denote the maximum degree of G, the number of maximal cliques, the size of the maximum clique, and the number of triangles of a vertex with degree D respectively. Finally, we apply our algorithm to the telecommunication customer-churn-prediction and the experimental results show that the application promotes the capabilities of the churn prediction system effectively.
This work is supported by the National Science Foundation of China under grant number 60402011.
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Wan, L., Wu, B., Du, N., Ye, Q., Chen, P. (2006). A New Algorithm for Enumerating All Maximal Cliques in Complex Network. In: Li, X., Zaïane, O.R., Li, Z. (eds) Advanced Data Mining and Applications. ADMA 2006. Lecture Notes in Computer Science(), vol 4093. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11811305_67
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DOI: https://doi.org/10.1007/11811305_67
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