Residuals-based subgraph detection with cue vertices

B. A. Miller, Stephen Kelley, R. Caceres, S. Smith
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引用次数: 5

Abstract

A common problem in modern graph analysis is the detection of communities, an example of which is the detection of a single anomalously dense subgraph. Recent results have demonstrated a fundamental limit for this problem when using spectral analysis of modularity. In this paper, we demonstrate the implication of these results on subgraph detection when a cue vertex is provided, indicating one of the vertices in the community of interest. Several recent algorithms for local community detection are applied in this context, and we compare their empirical performance to that of the simple method used to derive the theoretical detection limits.
基于残差的线索顶点子图检测
现代图分析中的一个常见问题是群体的检测,其中一个例子是单个异常密集子图的检测。最近的结果表明,当使用模块化的光谱分析时,这个问题的基本限制。在本文中,我们证明了这些结果对子图检测的意义,当提供线索顶点时,指示感兴趣社区中的一个顶点。在此背景下应用了几种最近的局部社区检测算法,并将它们的经验性能与用于推导理论检测限的简单方法进行了比较。
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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