团枚举算法的实现问题

T. Uno
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引用次数: 5

摘要

团是任意两个顶点相连的子图。Clique表示图中紧密连接的结构,因此用于捕获局部相关元素,如聚类、频繁模式、社区挖掘等。在这些应用程序中,经常使用团的枚举而不是优化。最近的应用有大规模的非常稀疏的图,因此团枚举的有效实现是必要的。在本文中,我们描述了获得高效团枚举实现的算法技术(而不是编码技术)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Implementation issues of clique enumeration algorithm
A clique is a subgraph in which any two vertices are connected. Clique represents a densely connected structure in the graph, thus used to capture the local related elements such as clustering, frequent patterns, community mining, and so on. In these applications, enumeration of cliques rather than optimization is frequently used. Recent applications have large scale very sparse graphs, thus efficient implementations for clique enumeration is necessary. In this paper, we describe the algorithm techniques (not coding techniques) for obtaining efficient clique enumeration implementations.
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