Spatial Scan Statistics for Graph Clustering [chapter]

Bei Wang, Jeff M. Phillips, Robert Schreiber, Dennis Wilkinson, Nina Mishra, Robert Tarjan
2008 Proceedings of the 2008 SIAM International Conference on Data Mining  
In this paper, we present a measure associated with detection and inference of statistically anomalous clusters of a graph based on the likelihood test of observed and expected edges in a subgraph. This measure is adapted from spatial scan statistics for point sets and provides quantitative assessment for clusters. We discuss some important properties of this statistic and its relation to modularity and Bregman divergences. We apply a simple clustering algorithm to find clusters with large
more » ... ers with large values of this measure in a variety of real-world data sets, and we illustrate its ability to identify statistically significant clusters of selected granularity.
doi:10.1137/1.9781611972788.66 dblp:conf/sdm/WangPSW08 fatcat:gmmabtcs4nd3pb65ws3w5chtdu