DefinePK

Abstract

Detecting communities from networks is one of the important
and challenging research topics in social network analysis, especially from
bipartite network. In unipartite network, communities are usually represented
as sets of nodes within which connections are dense but between which connections
are sparse. However, communities in unipartite networks are not suitable to
bipartite network, because there is only one-to-one correspondence between communities
of different types. In this study we propose an algorithm for detecting communities
from bipartite network based on ant colony optimization. Present algorithm allows
many-to-many correspondence between communities in different parts. Experimental
results demonstrate that tour algorithm can extract multi-facet communities
from bipartite networks and obtain high quality of community partitioning.