优化参数搜索,以在复杂系统的不断变化的网络中进行社区检测.
Italo'Ivo Lima Dias Pinto1, Javier Omar Garcia1, Kanika Bansal1,2
1US DEVCOM Army Research Laboratory, Aberdeen Proving Ground, Maryland 21005, USA.
Chaos (Woodbury, N.Y.)
|February 22, 2024
概括
本研究介绍了一种客观的方法来选择动态网络中社区检测的分辨率参数. 它通过最小化空间偏差和最大化尺度自由度来增强复杂系统的分析.
科学领域:
- 网络科学 网络科学
- 复杂系统分析 复杂系统分析
- 数据挖掘 数据挖掘
背景情况:
- 网络表示对于分析复杂系统至关重要.
- 了解网络中的时间动态是解码基础过程的关键.
- 社区检测算法对于研究时间网络变化至关重要,但依赖于主观参数选择.
研究的目的:
- 开发一种客观的方法来确定动态网络社区检测中的分辨率参数.
- 在复杂的系统中提高社区检测的准确性和可靠性.
- 为自动参数选择提供普遍适用的软件包.
主要方法:
- 介绍了一种基于自我组织和尺度不变原则的新方法.
- 提出了两个关键方法:尽量减少空间尺度偏差,最大限度地提高时间尺度自由度.
- 使用基准和现实世界网络数据集验证了该方法.
主要成果:
- 证明了拟议的目标参数选择方法的有效性.
- 展示了客观地确定动态网络分析的分辨率参数的能力.
- 开发了一个自动化软件包,用于各种复杂系统的实际应用.
结论:
- 开发的方法为动态网络社区检测提供了客观和数据驱动的参数选择方法.
- 这一进步通过提供可靠的社区结构,改善了复杂系统的分析.
- 该自动化软件有助于更广泛的应用,并增强了对时间网络动态的研究.
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