Quantitative function for community detection.
We propose a quantitative function for community partition -- i.e., modularity density or D value. We demonstrate that this quantitative function is superior to the widely used modularity Q and also prove its equivalence with the objective function of the kernel k means. Both theoretical and numerical results show that optimizing the new criterion not only can resolve detailed modules that existing approaches cannot achieve, but also can correctly identify the number of communities.
Li
Zhenping
Z
Beijing Wuzi University, Beijing, China.
Zhang
Shihua
S
Wang
Rui-Sheng
RS
Zhang
Xiang-Sun
XS
Chen
Luonan
L