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Computing Strong Articulation Points and Strong Bridges in Large Scale Graphs

机译:在大型图形中计算强铰接点和强桥梁

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Let G = (V, E) be a directed graph. A vertex v e V (respectively an edge e € E) is a strong articulation point (respectively a strong bridge) if its removal increases the number of strongly connected components of G. We implement and engineer the linear-time algorithms in [9] for computing all the strong articulation points and all the strong bridges of a directed graph. Our implementations are tested against real-world graphs taken from several application domains, including social networks, communication graphs, web graphs, peer2peer networks and product co-purchase graphs. The algorithms implemented turn out to be very efficient in practice, and are able to run on large scale graphs, i.e., on graphs with ten million vertices and half billion edges. Our experiments on such graphs highlight some properties of strong articulation points, which might be of independent interest.
机译:令G =(V,E)为有向图。如果顶点ve V的移除增加了G的强连通分量的数量,则顶点ve V(分别是边e€E)是一个强铰接点(分别是坚固的桥)。我们在[9]中实现并设计线性时间算法计算有向图的所有强关节点和所有强桥梁。我们的实现是针对来自多个应用程序领域的真实世界图进行测试的,这些领域包括社交网络,通信图,Web图,peer2peer网络和产品共同购买图。所实现的算法实际上在实践中非常有效,并且能够在大规模图上运行,即在具有一千万个顶点和五亿个边的图上运行。我们在此类图上进行的实验突出显示了强铰接点的某些属性,这些属性可能是独立引起的。

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