  In this paper, we propose a novel semi-parametric probabilistic model which
considers interactions between different communities and can provide more
information about the network topology besides correctly detecting communities.
By using an additional parameter, our model can not only detect community
structure but also detect pattern which is a generalization of common sense
network community structure. The prior parameter in our model reveals the
characteristics of patterns inside the network. Results on some widely known
data sets prove the efficiency of our model.
