Maximizing Modularity is hard
Data Analysis, Statistics and Probability
2007-05-23 v2 Statistical Mechanics
Physics and Society
Abstract
Several algorithms have been proposed to compute partitions of networks into communities that score high on a graph clustering index called modularity. While publications on these algorithms typically contain experimental evaluations to emphasize the plausibility of results, none of these algorithms has been shown to actually compute optimal partitions. We here settle the unknown complexity status of modularity maximization by showing that the corresponding decision version is NP-complete in the strong sense. As a consequence, any efficient, i.e. polynomial-time, algorithm is only heuristic and yields suboptimal partitions on many instances.
Cite
@article{arxiv.physics/0608255,
title = {Maximizing Modularity is hard},
author = {U. Brandes and D. Delling and M. Gaertler and R. Goerke and M. Hoefer and Z. Nikoloski and D. Wagner},
journal= {arXiv preprint arXiv:physics/0608255},
year = {2007}
}
Comments
10 pages, 1 figure