利用图的方向进行子图计数的若干要点(特邀演讲)

C. Seshadhri, Floris Geerts, Brecht Vandevoort
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引用次数: 1

摘要

子图计数是一个基本问题,它跨越了计算机科学的许多领域:数据库理论、逻辑、网络科学、数据挖掘和复杂性理论。给定一个大的输入图G和一个小的模式图H,我们希望计算H在G中出现的次数。最近,使用一种古老的(可能被忽视的?)技术重新兴起,这种技术定位G和H的边缘,然后结合使用暴力枚举和索引。这些定向技术似乎是两全其美。这些技术背后有严格的理论解释,它们也有出色的经验行为(在大型现实世界的图表上)。图的方向一次又一次地帮助解决了各种计算模型中的子图计数问题,比如采样、流、分布式等。在本文中,我们简要介绍了定向技术如何解决各种算法问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Some Vignettes on Subgraph Counting Using Graph Orientations (Invited Talk)
Subgraph counting is a fundamental problem that spans many areas in computer science: database theory, logic, network science, data mining, and complexity theory. Given a large input graph G and a small pattern graph H , we wish to count the number of occurrences of H in G . In recent times, there has been a resurgence on using an old (maybe overlooked?) technique of orienting the edges of G and H , and then using a combination of brute-force enumeration and indexing. These orientation techniques appear to give the best of both worlds. There is a rigorous theoretical explanation behind these techniques, and they also have excellent empirical behavior (on large real-world graphs). Time and again, graph orientations help solve subgraph counting problems in various computational models, be it sampling, streaming, distributed, etc. In this paper, we give some short vignettes on how the orientation technique solves a variety of algorithmic problems.
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