14 citations · 40 across the 10 of their papers we have counts for
3 papers · 1 filter
Generating realistic scaled complex networks
Christian L. Staudt, Michael Hamann, Alexander Gutfraind +2
Research on generative models is a central project in the emerging field of network science, and it studies how statistical patterns found in real networks could be generated by fo…
I/O-Efficient Generation of Massive Graphs Following the LFR Benchmark
Michael Hamann, Ulrich Meyer, Manuel Penschuck +2
LFR is a popular benchmark graph generator used to evaluate community detection algorithms. We present EM-LFR, the first external memory algorithm able to generate massive complex…
Structure-Preserving Sparsification Methods for Social Networks
Michael Hamann, Gerd Lindner, Henning Meyerhenke +2
Sparsification reduces the size of networks while preserving structural and statistical properties of interest. Various sparsifying algorithms have been proposed in different conte…