Single- and multi-level network sparsification by algebraic distance

Emmanuel John, Ilya Safro
2016 Journal of Complex Networks  
Network sparsification methods play an important role in modern network analysis when fast estimation of computationally expensive properties (such as the diameter, centrality indices, and paths) is required. We propose a method of network sparsification that preserves a wide range of structural properties. Depending on the analysis goals, the method allows to distinguish between local and global range edges that can be filtered out during the sparsification. First we rank edges by their
more » ... ic distances and then we sample them. We also introduce a multilevel framework for sparsification that can be used to control the sparsification process at various coarse-grained resolutions. Based primarily on the matrix-vector multiplications, our method is easily parallelized for different architectures.
doi:10.1093/comnet/cnw025 fatcat:2og6iqo56fg43hqvxeuu3cvw5i