betweenness.centrality.clustering    package:RBGL    R Documentation

_G_r_a_p_h _c_l_u_s_t_e_r_i_n_g _b_a_s_e_d _o_n _e_d_g_e _b_e_t_w_e_e_n_n_e_s_s _c_e_n_t_r_a_l_i_t_y

_D_e_s_c_r_i_p_t_i_o_n:

     Graph clustering based on edge betweenness centrality

_U_s_a_g_e:

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

_A_r_g_u_m_e_n_t_s:

       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

_D_e_t_a_i_l_s:

     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.

_V_a_l_u_e:

   edges: 

betweenness.centrality.clustering: 

_A_u_t_h_o_r(_s):

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

_R_e_f_e_r_e_n_c_e_s:

     Boost Graph Library by Siek et al.

_S_e_e _A_l_s_o:

_E_x_a_m_p_l_e_s:

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

