betweenness.centrality.clustering {RBGL}R Documentation

Graph clustering based on edge betweenness centrality

Description

Graph clustering based on edge betweenness centrality

Usage

betweenness.centrality.clustering(g, threshold = -1, normalize = T))

Arguments

g an instance of the graph class with edgemode “undirected”
threshold threshold to terminate clustering process
normalize boolean, when true, the threshold is compared with the normalized edge centrality based on the input graph; when false, the threshold is compared with the absolute edge centrality

Details

This algorithm implements graph clustering based on edge betweenness centrality. It is an iterative algorithm, where in each step it compute the edge betweenness centrality and removes the edge with the maximum betweenness centrality.

Value

edges
betweenness.centrality.clustering

Author(s)

Li Long <li.long@isb-sib.ch>

References

Boost Graph Library by Siek et al.

See Also

Examples

coex <- fromGXL(file(system.file("XML/conn.gxl",package="RBGL")))
coex@edgemode <- "undirected"
betweenness.centrality.clustering(coex)

[Package RBGL version 1.3.8 Index]