三角密集图的分解

Rishi Gupta, T. Roughgarden, C. Seshadhri
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引用次数: 38

摘要

高三角密度是社交网络的常见特征,即两跳路径中有一定比例属于三角形的图形属性。本文从结构的角度研究了三角密集图。我们建设性地证明了一个三角形密集图的有效部分包含在一个半径为2的密集子图的不相交并中。这个结果量化了三角形密集图与团的并集相似的程度。我们还证明了我们的算法在近似稳定的k中值实例中恢复种植聚类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Decompositions of triangle-dense graphs
High triangle density -- the graph property stating that a constant fraction of two-hop paths belong to a triangle -- is a common signature of social networks. This paper studies triangle-dense graphs from a structural perspective. We prove constructively that significant portions of a triangle-dense graph are contained in a disjoint union of dense, radius 2 subgraphs. This result quantifies the extent to which triangle-dense graphs resemble unions of cliques. We also show that our algorithm recovers planted clusterings in approximation-stable k-median instances.
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