使用Lazy Global Domination更快地找到最大k团
Finding Maximum k-Cliques Faster using Lazy Global Domination
摘要：
图中的团是一组顶点，其中每个顶点都与该组中的所有其他顶点相邻。k团放宽了这一要求，要求顶点彼此之间的距离在k以内，而不是直接相邻。理论上，最大团算法可以很容易地适用于解决最大k团问题。我们使用最先进的最大团算法的状态，这是可行的，在实践中，并引入一个懒惰的全球统治规则，有时大大减少了搜索空间。我们包括一系列真实世界和基准图的实验结果，以及随机图的详细介绍。
英文摘要：
A clique in a graph is a set of vertices, each of which is adjacent to every other vertex in this set. A k-clique relaxes this requirement, requiring vertices to be within a distance k of each other, rather than directly adjacent. In theory, a maximum clique algorithm can easily be adapted to solve the maximum k-clique problem. We use a state of the art maximum clique algorithm to show that this is feasible in practice, and introduce a lazy global domination rule which sometimes vastly reduces the search space. We include experimental results for a range of real-world and benchmark graphs, and a detailed look at random graphs.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
