Detecting non-uniform clusters in large-scale interaction graphs.

Graph clustering becomes difficult as the graph size and complexity increase. In particular, in interaction graphs, the clusters are small and the data on the underlying interaction are not only complex, but also noisy due to the lack of information and experimental errors. The graphs representing such data consist of (possibly overlapping) clusters of non-uniform size with some false positive and false negative links.