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复杂网络深度重叠结构的发现

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为了更好地了解网络,以相似度为基础,让节点选择多个相似节点形成相似节点对,通过蒙卡模拟结果提出了基于最大节点相似度和度的配对算法发现了网络的重叠社团结构.利用多级最相似度继续优化社团结构,找出了网络社团的深层重叠结构和子社团结构.提出的算法从真实网络形成社团的原因出发发现了网络的重叠结构,并且进一步优化社团结构,发现了网络的深层重叠社团结构和其中的子社团结构.
Discovery of Deep Overlapping Structures in Complex Networks
In order to better understand the network,based on the similarity,let the nodes select multiple similar nodes to form similar node pairs.Through the Monte Carlo simulation results,a pairing algorithm based on the maximum node similarity and degree is proposed to discover the o-verlapping community structure of the network.Using multi-level most similarity to continue to optimize the community structure,find out the deep overlapping structure and sub-community structure of the network community.The proposed algorithm discovers the overlapping structure of the network based on the reason why the real network forms a community,and further optimi-zes the community structure,discovering the deep overlapping community structure of the net-work and its sub-community structure.

complex networkcommunity structuredeep overlapping structuresub-community structure

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三峡大学理学院,湖北宜昌 443002

复杂网络 社团结构 深度重叠结构 子社团结构

国家自然科学基金

11547003

2024

复杂系统与复杂性科学
青岛大学

复杂系统与复杂性科学

CSTPCD北大核心
影响因子:0.798
ISSN:1672-3813
年,卷(期):2024.21(2)