论文标题
表征复杂网络中的循环结构
Characterizing cycle structure in complex networks
论文作者
论文摘要
周期是最简单的结构，它在网络动力学中带来了网络连接性和反馈效果的冗余路径。本文着眼于循环结构，定义了一个名为“周期矩阵”的新矩阵，以表示网络的循环信息，而索引（命名为循环比率）来量化节点的重要性。实际网络的实验表明，除了众所周知的基准指标外，周期比还包含丰富的信息，例如，按周期比率划分的节点排名与按程度，h-索引，corentes，coreness，interness和表达式排名的排名差异很大，而排名划分为h-index，h-index，coreness与彼此非常相似。关于识别维持网络连接，促进网络同步的重要节点的广泛实验，并最大程度地提高了传播的早期覆盖范围，表明周期比与其他基准相比，循环比与之间的竞争能力更高。我们认为，对周期结构的深入分析可能会产生网络科学的新见解，指标，模型和算法。
Cycle is the simplest structure that brings redundant paths in network connectivity and feedback effects in network dynamics. Focusing on cycle structure, this paper defines a new matrix, named cycle number matrix, to represent cycle information of a network, and an index, named cycle ratio, to quantify the node importance. Experiments on real networks suggest that cycle ratio contains rich information in addition to well-known benchmark indices, for example, the node rankings by cycle ratio are largely different from rankings by degree, H-index, coreness, betweenness and articulation ranking, while the rankings by degree, H-index, coreness are very similar to each other. Extensive experiments on identifying vital nodes that maintain network connectivity, facilitate network synchronization and maximize the early reach of spreading show that cycle ratio is competitive to betweenness and overall better than other benchmarks. We believe the in-depth analyses on cycle structure may yield novel insights, metrics, models and algorithms for network science.
