Computing (1+epsilon)-Approximate Degeneracy in Sublinear Time

Valerie King, Alex Thomo, Quinton Yong
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引用次数: 1

Abstract

The problem of finding the degeneracy of a graph is a subproblem of the k-core decomposition problem. In this paper, we present a (1 + epsilon)-approximate solution to the degeneracy problem which runs in O(n log n) time, sublinear in the input size for dense graphs, by sampling a small number of neighbors adjacent to high degree nodes. This improves upon the previous work on sublinear approximate degeneracy, which implies a (4 + epsilon)-approximate ~O(n) solution. Our algorithm can be extended to an approximate O(n log n) time solution to the k-core decomposition problem. We also explore the use of our approximate algorithm as a technique for speeding up exact degeneracy computation. We prove theoretical guarantees of our algorithm and provide optimizations, which improve the running time of our algorithm in practice. Experiments on massive real-world web graphs show that our algorithm performs significantly faster than previous methods for computing degeneracy.
计算(1+epsilon)-亚线性时间内的近似退化
求图的退化问题是k核分解问题的一个子问题。在本文中,我们提出了一个(1 + epsilon)-近似解的退化问题,运行在O(n log n)时间,在密集图的输入大小是次线性的,通过采样少量的邻居相邻的高次节点。这改进了以前关于次线性近似退化的工作,这意味着(4 + epsilon)-近似~O(n)解。我们的算法可以扩展到k核分解问题的近似O(n log n)时间解。我们还探索了近似算法作为加速精确退化计算的技术的使用。证明了算法的理论保证,并对算法进行了优化,提高了算法在实践中的运行时间。在大量真实网络图上的实验表明,我们的算法比以前计算简并度的方法要快得多。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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