On Feasibility of Graph Spectrum-based Frequent Sub-graph Mining

抄録

We analytically and computationally assessed the performance of the graph spectrum based isomorphism identification, and applied the results to prune redundant candidate enumeration in a graph mining algorithm gSpan. The advantageous conditions to gain significant performance of the graph mining have been clarified in this study.