使用图案进行定向网络比较
Chenwei Xie1, Qiao Ke1, Haoyu Chen1
1Research Center for Complexity Sciences, Hangzhou Normal University, Hangzhou 311121, China.
Entropy (Basel, Switzerland)
|February 23, 2024
概括
这项研究引入了一种新的方法来比较使用动机的定向网络. 它有效地捕捉了本地,全球和更高层次的网络差异,优于现有的方法.
科学领域:
- 网络科学 网络科学
- 图形理论 图形理论
- 数据分析 数据分析
背景情况:
- 比较网络至关重要,但具有挑战性,特别是针对性网络.
- 现有的方法往往忽略了方向性和高级网络属性.
- 许多现实世界的网络 (生物,社会,运输) 本质上是有针对性的.
研究的目的:
- 开发一种基于动机的方法来比较定向网络.
- 为了捕捉本地,全球和更高层次的网络差异.
- 为了解决现有的拓比较方法的局限性.
主要方法:
- 构建节点特定的图案分布向量.
- 使用Jensen-Shannon分歧来量化网络不相似性.
- 将该方法应用于现实世界的定向网络及其零/扰乱模型.
主要成果:
- 拟议的方法有效地捕捉了各种网络差异.
- 在最先进的基线方法上表现出优越性.
- 在各种参数设置中展示了强度.
结论:
- 基于图案的方法为有针对性的网络比较提供了一个强大的工具.
- 这种方法可以增强对复杂网络结构的理解.
- 它为网络分析提供了一个强大而通用的框架.
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