具有优先附属性和附属性的附属网络的建模和分析
Alexey Nikolaev1, Saad Mneimneh1,2
1Department of Computer Science, The Graduate Center of CUNY, 365 5th Avenue, New York, New York 10016, USA.
Physical review. E
|August 16, 2023
概括
我们介绍了关联网络的新型优先附加模型,揭示了超图和简化复杂表示中的权力法度分布. 该框架使得用于模拟的各种网络结构的合成生成成为可能.
科学领域:
- 网络科学 网络科学
- 复杂的系统复杂的系统.
- 数据挖掘 数据挖掘
背景情况:
- 优先附加模型基于节点程度的网络增长.
- 关联网络代表了节点组,在图表视图中通常缺乏权力法度分布.
- 现有的模型不能完全捕捉到关联网络的结构.
研究的目的:
- 建议为附属网络量身定制的优先附加机制.
- 在这些网络的超图和简化复杂表示中展示权力法特征的出现.
- 为合成生成多样化的加盟网络结构提供框架.
主要方法:
- 为关联网络开发了一种优先附加模式.
- 利用超图和简化复杂表示来分析网络属性.
- 研究了算法和分析特征,包括隐含的偏好附加和附加.
主要成果:
- 拟议的模型在超图和简化复杂视图中展示了权力法度分布.
- 该模型展示了隐含的优先附加和局部属性.
- 在简化的复合体中,附加允许隐式删除附属关系,并控制大小分布.
结论:
- 新的优惠附加模式有效地捕捉了附属网络的特点.
- 超图和简化复杂表示对于观察权力定律行为至关重要.
- 该框架作为模拟和研究关联网络的多功能工具.
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