A new algorithm for enumerating all maximal cliques in complex network

  • Authors:

  • Li Wan;Bin Wu;Nan Du;Qi Ye;Ping Chen

  • Affiliations:

  • Telecommunication Software Engineering Center, School of Computer Science and Technology, Beijing University of Posts and Telecommunications, Beijing, China;Telecommunication Software Engineering Center, School of Computer Science and Technology, Beijing University of Posts and Telecommunications, Beijing, China;Telecommunication Software Engineering Center, School of Computer Science and Technology, Beijing University of Posts and Telecommunications, Beijing, China;Telecommunication Software Engineering Center, School of Computer Science and Technology, Beijing University of Posts and Telecommunications, Beijing, China;Telecommunication Software Engineering Center, School of Computer Science and Technology, Beijing University of Posts and Telecommunications, Beijing, China

  • Venue:
  • ADMA'06 Proceedings of the Second international conference on Advanced Data Mining and Applications
  • Year:
  • 2006

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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.