WalkSum: Graph Summarization for Accurate Random Walks

Graph summarization is effective when providing a graph to a third party while protecting the detailed topology. Although existing methods emphasize the topological similarity of the summary graph and the original graph, the analysis results of the two graphs are not consistent. In this paper, we propose a method for generating summary graphs to provide consistency in random walk-based analysis. In particular, our method, WalkSum, determines supernodes such that the random walks are unlikely to transition between them and stay within them. It also determines the weight of the superedges, considering the transition probabilities in the original graph. Our evaluations clarified that WalkSum achieves high accuracy over a wide range of summary rates. Compared to one of the state-of-the-art methods, we found that WalkSum is up to 15 % more accurate.