Stable Subgraph Isomorphism Search in Temporal Networks

In this paper, we study a new problem of seeking stable subgraph isomorphisms for a query graph in a temporal graph. To solve our problem, we first develop a pruning-based search algorithm using several new pruning tricks to prune the unpromising matching results during the search procedure. To further improve the efficiency, we propose a novel index structure called
${{\mathsf {BCCIndex}}}$
, based on an idea of bi-connected component decomposition of the query graph, which can efficiently support the stable subgraph isomorphism search. Equipped with the
${{\mathsf {BCCIndex}}}$
, we present an efficient query processing algorithm based on a carefully designed tree join technique. We conduct extensive experiments to evaluate our algorithms on four large real-life datasets, and the results demonstrate the efficiency and effectiveness of our algorithms.