Publication: Multistep greedy algorithm identifies community structure in real-world and computer-generated networks.
Multistep greedy algorithm identifies community structure in real-world and computer-generated networks.
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Schuetz, P., & Caflisch, A. (2008). Multistep greedy algorithm identifies community structure in real-world and computer-generated networks. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics, 78(026112), 026112–1. https://doi.org/10.1103/PhysRevE.78.026112
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We have recently introduced a multistep extension of the greedy algorithm for modularity optimization. The extension is based on the idea that merging l pairs of communities (l>1) at each iteration prevents premature condensation into few large communities. Here, an empirical formula is presented for the choice of the step width l that generates partitions with (close to) optimal modularity for 17 real-world and 1100 computer-generated networks. Furthermore, an in-depth analysis of the communities of two real-world networks (the metab
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- Schuetz, P
- Caflisch, A
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Citations
Schuetz, P., & Caflisch, A. (2008). Multistep greedy algorithm identifies community structure in real-world and computer-generated networks. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics, 78(026112), 026112–1. https://doi.org/10.1103/PhysRevE.78.026112
