  The primary objective of graph pattern matching is to find all appearances of
an input graph pattern query in a large data graph. Such appearances are called
matches. In this paper, we are interested in finding matches of interaction
patterns in temporal graphs. To this end, we propose a hybrid approach that
achieves effective filtering of potential matches based both on structure and
time. Our approach exploits a graph representation where edges are ordered by
time. We present experiments with real datasets that illustrate the efficiency
of our approach.
