Subgraph isomorphism detection in polynomial time on preprocessed model graphs

Abstract

In this paper, a new method for graph and subgraph isomorphism detection based on a decision tree representation is proposed. The decision tree is generated off-line from a priori known model graphs. At run time the decision tree is used to detect all graph and subgraph isomorphisms from an input graph to any of the model graphs in time that is only polynomial in the size of the graphs and independent of the number of model graphs. However, the decision tree is of exponential size. In order to reduce the size of the decision tree, we propose two pruning techniques. Experimental results confirming the efficiency of the method will be given.