FINDING FREQUENT SUBPATHS IN A G RAPH

Abstract

The problem considered is that of finding frequent subpaths of a database of paths in a fixed undirected graph. This problem arises in applications such as predicting congestion in network and vehicular traffic. An algorithm, called AFS, based on the classic frequent itemset mining algorithm Apriori is developed, but with significantly improved efficiency over Apriori from exponential in transaction size to quadratic through exploiting the underlying graph structure. This efficiency makes AFS feasible for practical input path sizes. It is also proved that a natural generalization of the frequent subpaths problem is not amenable to any solution quicker than Apriori.