Co-clustering directed graphs to discover asymmetries and directional communities.

ABSTRACT: In directed graphs, relationships are asymmetric and these asymmetries contain essential structural information about the graph. Directed relationships lead to a new type of clustering that is not feasible in undirected graphs. We propose a spectral co-clustering algorithm called di-sim for asymmetry discovery and directional clustering. A Stochastic co-Blockmodel is introduced to show favorable properties of di-sim To account for the sparse and highly heterogeneous nature of directed networks, di-sim uses the regularized graph Laplacian and projects the rows of the eigenvector matrix onto the sphere. A nodewise asymmetry score and di-sim are used to analyze the clustering asymmetries in the networks of Enron emails, political blogs, and the Caenorhabditiselegans chemical con

SUBMITTER: Rohe K 

PROVIDER: S-EPMC5111689 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature