论文标题
计算（1+epsilon） - 均方根时期的脱氧化性
Computing (1+epsilon)-Approximate Degeneracy in Sublinear Time
论文作者
论文摘要
找到图的退化的问题是K核分解问题的子问题。在本文中，我们提出了一个（1 + epsilon） - 在O（n log n）时间内运行的退化问题的解决方案，通过抽样少数与高度节点相邻的邻居，在输入尺寸中以sublinear进行sublinear。我们的算法也可以将其扩展到O（n log n）时间解决方案到K核分解问题。这对Bhattacharya等人的方法有所改善，这意味着（4 + epsilon） - 对脱落问题的溶液（N）解决方案，我们的技术类似于其他素描方法，这些方法使用sublinear空间用于K核和退化。我们证明了算法的理论保证并提供了优化，从而改善了我们实践中算法的运行时间。大规模现实世界网络图上的实验表明，我们的算法的性能要快于以前的计算堕落方法，包括Li等人的2022精确退化算法。
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. Our algorithm can also be extended to an O(n log n) time solution to the k-core decomposition problem. This improves upon the method by Bhattacharya et al., which implies a (4 + epsilon)-approximate ~O(n) solution to the degeneracy problem, and our techniques are similar to other sketching methods which use sublinear space for k-core and degeneracy. 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, including the 2022 exact degeneracy algorithm by Li et al.
