Structural Graph Indexing for Mining Complex Networks

Systems such as proteins, chemical compounds, and the Internet are being modeled as complex networks to identify local and global characteristics of the system. In many instances, these graphs are very large in size presenting challenges in their analysis. Hence, graph indexing techniques are developed to enhance various graph mining algorithms. In this paper, we propose a new Structural Graph Indexing (SGI) technique that does not limit the number of nodes in indexing to provide an alternative tool for graph mining algorithms. As indexing feature, we use common graph structures, namely, star, complete bipartite, triangle and clique, that frequently appear in protein, chemical compound, and Internet graphs. Note that, SGI lists all substructures matching structure formulations and other graph structures can be identified and added to the SGI.