基于簇扩展的簇网络模型

IF 0.9 4区数学 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Journal of Combinatorial Optimization Pub Date : 2024-05-20 DOI:10.1007/s10878-024-01178-y

Anthony Bonato, Ryan Cushman, Trent G. Marbach, Zhiyuan Zhang

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引用次数: 0

摘要

小群模型通过扩展小群来模拟网络演化，小群代表社交网络中高度互动的群体。在每个时间步中，新的顶点会被添加到现有的具有规定顺序的小群附近。该模型展现了社交网络的几个特征，如密集化、短距离、不良频谱扩展和高局部聚类。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

The frustum network model based on clique extension

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The frustum network model based on clique extension

The frustum model simulates network evolution by extending cliques, which represent highly interacting groups in social networks. In each time-step, new vertices are added adjacent to existing cliques of prescribed order. The model exhibits several features of social networks, such as densification, short distances, bad spectral expansion, and high local clustering.

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来源期刊

Journal of Combinatorial Optimization 数学-计算机：跨学科应用

CiteScore

2.00

自引率

10.00%

发文量

审稿时长

6 months

期刊介绍： The objective of Journal of Combinatorial Optimization is to advance and promote the theory and applications of combinatorial optimization, which is an area of research at the intersection of applied mathematics, computer science, and operations research and which overlaps with many other areas such as computation complexity, computational biology, VLSI design, communication networks, and management science. It includes complexity analysis and algorithm design for combinatorial optimization problems, numerical experiments and problem discovery with applications in science and engineering. The Journal of Combinatorial Optimization publishes refereed papers dealing with all theoretical, computational and applied aspects of combinatorial optimization. It also publishes reviews of appropriate books and special issues of journals.