  In big data times, massive datasets often carry different relationships among
the same group of nodes, analyzing on these heterogeneous relationships may
give us a window to peek the essential relationships among nodes. In this
paper, first of all we propose a new metric "similarity rate" in order to
capture the changing rate of similarities between node-pairs though all
networks; secondly, we try to use this new metric to uncover essential
relationships between node-pairs which essential relationships are often hidden
and hard to get. From experiments study of Indonesian Terrorists dataset, this
new metric similarity rate function well for giving us a way to uncover
essential relationships from lots of appearances.
