Finding and Visualizing Graph Clusters Using PageRank Optimization

We give algorithms for finding graph clusters and drawing graphs, highlighting local community structure within the context of a larger network. For a given graph G, we use the personalized PageRank vectors to determine a set of clusters, by optimizing the jumping parameter subject to several cluster variance measures in order to capture the graph structure according to PageRank. We then give a graph visualization algorithm for the clusters using PageRank-based coordinates. Several drawings of real-world data are given, illustrating the partition and local community structure.

• Type: Journal
• Year: 2010
• Where: WAW
• Authors: Fan Chung Graham, Alexander Tsiatas
• Keywords: Algorithms, Graph Visualization Algorithm, Local Community Structure, Personalized Pagerank Vectors, WAW 2010