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Fast Algorithms for the Maximum Clique Problem on Massive Sparse Graphs

机译:大规模稀疏图上最大集团问题的快速算法

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The maximum clique problem is a well known NP-Hard problem with applications in data mining, network analysis, information retrieval and many other areas related to the World Wide Web. There exist several algorithms for the problem with acceptable runtimes for certain classes of graphs, but many of them are infeasible for massive graphs. We present a new exact algorithm that employs novel pruning techniques and is able to quickly find maximum cliques in large sparse graphs. Extensive experiments on different kinds of synthetic and real-world graphs show that our new algorithm can be orders of magnitude faster than existing algorithms. We also present a heuristic that runs orders of magnitude faster than the exact algorithm while providing optimal or near-optimal solutions.
机译:最大派系问题是一个众所周知的NP-Hard问题,它在数据挖掘,网络分析,信息检索和许多其他与万维网有关的领域中都有应用。对于某些类别的图,存在几种具有可接受的运行时间的问题的算法,但是其中许多算法对于大型图是不可行的。我们提出了一种新的精确算法,该算法采用了新颖的修剪技术,并且能够在大型稀疏图中快速找到最大团。在不同种类的合成图和真实世界图上进行的大量实验表明,我们的新算法比现有算法的速度快几个数量级。我们还提出了一种启发式算法,其运行速度比精确算法快了几个数量级,同时提供了最佳或接近最佳的解决方案。

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