ScholarGate
助手
Process / pipelineNetwork structure

k-核分解

k-核分解是一种图论方法,它将网络中的顶点划分为一系列嵌套的子图,称为 k-核。k-核是最大的子图,其中每个顶点在该子图内至少有 k 个邻居。该方法由 Stephen B. Seidman 于 1983 年提出,它为每个顶点分配一个核心度(coreness)数值,该数值捕捉了顶点相对于图的局部连通性的结构中心性。

在 MethodMind 中打开即将推出视频即将推出Download slides

阅读完整方法

仅限会员

使用免费账户登录即可阅读本节。

登录

Method map

The neighbourhood of related methods — select a node to explore.

来源

  1. Seidman, S. B. (1983). Network structure and minimum degree. Social Networks, 5(3), 269–287. DOI: 10.1016/0378-8733(83)90028-X

如何引用本页

ScholarGate. (2026, June 2). k-Core Decomposition of Networks. ScholarGate. https://scholargate.app/zh/network-analysis/k-core-decomposition

Which method?

Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.

Compare side by side
ScholarGatek-Core Decomposition (k-Core Decomposition of Networks). 于 2026-06-15 检索自 https://scholargate.app/zh/network-analysis/k-core-decomposition · 数据集: https://doi.org/10.5281/zenodo.20539026