561
个编辑
更改
→Cross-clique centrality
==Cross-clique centrality==
==Cross-clique centrality==
交叉团中心性
'''Cross-clique centrality''' of a single node in a complex graph determines the connectivity of a node to different [[clique (graph theory)|clique]]s. A node with high cross-clique connectivity facilitates the propagation of information or disease in a graph. Cliques are subgraphs in which every node is connected to every other node in the clique. The cross-clique connectivity of a node <math>v</math> for a given graph <math>G:=(V,E)</math> with <math>|V|</math> vertices and <math>|E|</math> edges, is defined as <math>X(v)</math> where <math>X(v)</math> is the number of cliques to which vertex <math>v</math> belongs. This measure was used in <ref name="xssworms">{{cite journal |last1 = Faghani|first1 = Mohamamd Reza| year=2013| title = A Study of XSS Worm Propagation and Detection Mechanisms in Online Social Networks | journal = IEEE Transactions on Information Forensics and Security|volume = 8|issue = 11|pages = 1815–1826|doi = 10.1109/TIFS.2013.2280884}}</ref> but was first proposed by Everett and Borgatti in 1998 where they called it clique-overlap centrality.
'''Cross-clique centrality''' of a single node in a complex graph determines the connectivity of a node to different [[clique (graph theory)|clique]]s. A node with high cross-clique connectivity facilitates the propagation of information or disease in a graph. Cliques are subgraphs in which every node is connected to every other node in the clique. The cross-clique connectivity of a node <math>v</math> for a given graph <math>G:=(V,E)</math> with <math>|V|</math> vertices and <math>|E|</math> edges, is defined as <math>X(v)</math> where <math>X(v)</math> is the number of cliques to which vertex <math>v</math> belongs. This measure was used in <ref name="xssworms">{{cite journal |last1 = Faghani|first1 = Mohamamd Reza| year=2013| title = A Study of XSS Worm Propagation and Detection Mechanisms in Online Social Networks | journal = IEEE Transactions on Information Forensics and Security|volume = 8|issue = 11|pages = 1815–1826|doi = 10.1109/TIFS.2013.2280884}}</ref> but was first proposed by Everett and Borgatti in 1998 where they called it clique-overlap centrality.
Cross-clique centrality of a single node in a complex graph determines the connectivity of a node to different cliques. A node with high cross-clique connectivity facilitates the propagation of information or disease in a graph. Cliques are subgraphs in which every node is connected to every other node in the clique. The cross-clique connectivity of a node <math>v</math> for a given graph <math>G:=(V,E)</math> with <math>|V|</math> vertices and <math>|E|</math> edges, is defined as <math>X(v)</math> where <math>X(v)</math> is the number of cliques to which vertex <math>v</math> belongs. This measure was used in but was first proposed by Everett and Borgatti in 1998 where they called it clique-overlap centrality.
Cross-clique centrality of a single node in a complex graph determines the connectivity of a node to different cliques. A node with high cross-clique connectivity facilitates the propagation of information or disease in a graph. Cliques are subgraphs in which every node is connected to every other node in the clique. The cross-clique connectivity of a node <math>v</math> for a given graph <math>G:=(V,E)</math> with <math>|V|</math> vertices and <math>|E|</math> edges, is defined as <math>X(v)</math> where <math>X(v)</math> is the number of cliques to which vertex <math>v</math> belongs. This measure was used in but was first proposed by Everett and Borgatti in 1998 where they called it clique-overlap centrality.
复杂图中单个节点的跨团中心性决定了一个节点与不同团的连通性。具有高度跨团连通性的节点有利于信息或疾病在图中的传播。团是一种子图，团中的每个节点都与团中的其他节点相连。对于一个给定的图 g: = (v，e) </math > 与 < math > | v | </math > 顶点和 < math > | e | </math > 边的交叉团连通性，定义为 < math > x (v) </math > x (v) </math > 其中 < math > x (v) </math > 是 < math > v </math > 所属的顶点团数。这个测度在年被使用，但是在1998年由 Everett 和 Borgatti 首次提出，他们称之为派系重叠中心性。
复杂图中单个节点的跨团中心性决定了一个节点与不同团的连通性。具有高度跨团连通性的节点有利于信息或疾病在图中的传播。团是一种子图，团中的每个节点都与团中的其他节点相连。对于一个给定的图 g: = (v，e) </math > 与 < math > | v | </math > 顶点和 < math > | e | </math > 边的交叉团连通性，定义为 < math > x (v) </math > x (v) </math > 其中 < math > x (v) </math > 是 < math > v </math > 所属的顶点团数。这个测度应用日久，但是在1998年由 Everett 和 Borgatti 首次提出，他们称之为派系重叠中心性。
==Freeman centralization==
==Freeman centralization==