网络的全球分解成由本地枢纽组成的多个核心
Wonhee Jeong1, Unjong Yu2, Sang Hoon Lee1,3,4
1Gyeongsang National University, The Research Institute of Natural Science, Jinju 52828, Korea.
Physical review. E
|June 19, 2025
概括
这项研究引入了一种新的网络分解方法,以揭示隐藏的多层次核心-外围结构. 该技术有效地将网络骨干与外分开,揭示了层次组织和关键的本地子结构.
科学领域:
- 网络科学 网络科学
- 复杂系统分析 复杂系统分析
- 图形理论 图形理论
背景情况:
- 网络在各个领域都具有根本性的作用,模拟具有节点和相互连接的复杂系统.
- 了解网络结构,特别是核心-外围组织,对于分析系统行为至关重要.
- 现有的分解方法可能无法完全捕捉当地结构细微差别.
研究的目的:
- 引入一种新的网络分解方案,以揭示多层次的核心-外围结构.
- 开发一种基于局部节点枢纽中心性和边缘修剪的方法.
- 为了证明在识别本地基层结构方面比传统方法的优势.
主要方法:
- 一个网络分解方案,利用本地定义的节点枢纽中心性.
- 基于局部连接的边缘修剪技术,以确定断裂点.
- 代移除局部连接最少的节点以揭示层次结构.
- 集成与网络社区检测,用于高级应用程序.
主要成果:
- 基于枢纽中心性的边缘修剪有效地将网络分成骨干和外结构.
- 局部边缘分解方法揭示了一个类似洋的等级结构.
- 与k-核心分解相比,拟议的方法在发现局部关键的子结构方面表现优越.
- 在检测多个核心-外围结构和分解超级节点网络方面成功应用.
结论:
- 开发的网络分解方法提供了一种强大的方法来揭示多层次的核心-外围结构.
- 该方法依赖于本地信息,在识别关键网络组件方面具有优势.
- 这种技术通过揭示层次组织和局部重要性来增强复杂系统的分析.
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