论文标题
在大型网络中找到最大集团
Finding Maximum Cliques in Large Networks
论文作者
论文摘要
有许多方法可以在大型网络中找到最大（或最大）集团。由于组合学的性质，随着图表中的顶点数量的增加，计算变得昂贵。因此，需要有效的算法找到最大的集团。在本文中，我们提出了一种显着降低图的顺序的绘制方法，因此可以识别大量图的最大集团，否则该计算是不可避免的，以找到最大值。我们使用此还原找到了最大（或最大）集团的最大（或最大）集团的边界。我们在现实生活中以及Erdös-Renyi随机图上演示了我们的方法。
There are many methods to find a maximum (or maximal) clique in large networks. Due to the nature of combinatorics, computation becomes exponentially expensive as the number of vertices in a graph increases. Thus, there is a need for efficient algorithms to find a maximum clique. In this paper, we present a graph reduction method that significantly reduces the order of a graph, and so enables the identification of a maximum clique in graphs of large order, that would otherwise be computational infeasible to find the maximum. We find bounds of the maximum (or maximal) clique using this reduction. We demonstrate our method on real-life social networks and also on Erdös-Renyi random graphs.
