Considerations about multistep community detection
Abstract
The problem and implications of community detection in networks have raised a huge attention, for its important applications in both natural and social sciences. A number of algorithms has been developed to solve this problem, addressing either speed optimization or the quality of the partitions calculated. In this paper we propose a multi-step procedure bridging the fastest, but less accurate algorithms (coarse clustering), with the slowest, most effective ones (refinement). By adopting heuristic ranking of the nodes, and classifying a fraction of them as `critical', a refinement step can be restricted to this subset of the network, thus saving computational time. Preliminary numerical results are discussed, showing improvement of the final partition.
Cite
@article{arxiv.1402.6508,
title = {Considerations about multistep community detection},
author = {Cristian Bisconti and Angelo Corallo and Laura Fortunato and Antonio A. Gentile},
journal= {arXiv preprint arXiv:1402.6508},
year = {2014}
}
Comments
12 pages