  Computing meaningful clusters of nodes is crucial to analyze large networks.
In this paper, we present a pairwise node similarity measure that allows to
extract roles, i.e. group of nodes sharing similar flow patterns within a
network. We propose a low rank iterative scheme to approximate the similarity
measure for very large networks. Finally, we show that our low rank similarity
score successfully extracts the different roles in random graphs and that its
performances are similar to the pairwise similarity measure.
