Finding the most prominent group in complex networks

Rami Puzis, Yuval Elovici, Shlomi Dolev

AI communications 20 (4), 287-296, 2007

In many applications we are required to locate the most prominent group of vertices in a complex network. Group Betweenness Centrality can be used to evaluate the prominence of a group of vertices. Evaluating the Betweenness of every possible group in order to find the most prominent is not computationally feasible for large networks. In this paper we present two algorithms for finding the most prominent group. The first algorithm is based on heuristic search and the second is based on iterative greedy choice of vertices. The algorithms were evaluated on random and scale-free networks. Empirical evaluation suggests that the greedy algorithm results were negligibly below the optimal result. In addition, both algorithms performed better on scale-free networks: heuristic search was faster and the greedy algorithm produced more accurate results. The greedy algorithm was applied for optimizing deployment of …