A novel method to measure graph similarity

Abstract

A novel method to measure the graph similarity is proposed, where the labels, in-degrees, and out-degrees of the vertices in the graph are comprehensively considered in order to conquer the high complexity and information loss in the measurement process. In this proposal, the graph is decomposed into a generalized tree and its similarity can be measured by computing the cost of the node sequence triples in the generalized tree. The proposed method decreases the computational complexity to O(n2) in comparison with the other available graph similarity methods. An example is provided to illustrate that the method is feasible and effective.