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Isomorphism Testing via Polynomial-Time Graph Extensions

机译:通过多项式时间图扩展进行同构测试

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This paper deals with algorithms for detecting graph isomorphism (GI) properties. The GI literature consists of numerous research directions, from highly theoretical studies (e.g. defining the GI complexity class) to very practical applications (pattern recognition, image processing). We first present the context of our work and provide a brief overview of various algorithms developed in such disparate contexts. Compared to well-known NP-complete problems, GI is only rarely tackled with general-purpose combinatorial optimization techniques; however, classical search algorithms are commonly applied to graph matching (GM). We show that, by specifically focusing on exploiting isomorphism properties, classical GM heuristics can become very useful for GI. We introduce a polynomial graph extension procedure that provides a graph coloring (labeling) capable of rapidly guiding a simple-but-effective heuristic toward the solution. The resulting algorithm (GI-Ext) is quite simple, very fast and practical: it solves GI within a time in the region of O(|V|3) for numerous graph classes, including difficult (dense and regular) graphs with up to 20.000 vertices and 200.000.000 edges. GI-Ext can compete with recent state-of-the-art GI algorithms based on well-established GI techniques (e.g. canonical labeling) refined over the last three decades. In addition, GI-Ext also solves certain GM problems, e.g. it detects important isomorphic structures induced in non-isomorphic graphs.
机译:本文介绍了用于检测图同构(GI)属性的算法。地理标志文献包括许多研究方向,从高度理论的研究(例如定义地理标志复杂度类别)到非常实际的应用(模式识别,图像处理)。我们首先介绍我们的工作环境,并简要概述在这种不同环境中开发的各种算法。与著名的NP完全问题相比,通用组合优化技术很少解决GI。但是,经典搜索算法通常应用于图匹配(GM)。我们表明,通过专门关注同构性质,经典GM启发式方法对于GI可能变得非常有用。我们引入了多项式图扩展过程,该过程提供了能够快速将简单但有效的启发式方法引导至解决方案的图着色(标记)功能。生成的算法(GI-Ext)非常简单,非常快速且实用:对于许多图类,包括困难(密集和规则),它都能在O(| V | 3 )范围内求解GI。最多具有20.000个顶点和200.000.000条边的图形。 GI-Ext可以与最近三十年来基于完善的GI技术(例如规范标签)的最新GI算法相竞争。此外,GI-Ext还解决了某些GM问题,例如它检测在非同构图中诱导的重要同构结构。

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