Maximizing Modularity is hard

Simple item page
dc.creatorBrandes, U.
dc.creatorDelling, D.
dc.creatorGaertler, M.
dc.creatorGoerke, R.
dc.creatorHoefer, M.
dc.creatorNikoloski, Z.
dc.creatorWagner, D.
dc.date2006-08-25
dc.date2006-08-30
dc.date.accessioned2026-07-07T07:25:54Z
dc.date.available2026-07-07T07:25:54Z
dc.descriptionSeveral 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.
dc.description10 pages, 1 figure
dc.identifierhttps://arxiv.org/abs/physics/0608255
dc.identifierhttp://arxiv.org/abs/physics/0608255
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/116889
dc.subjectData Analysis, Statistics and Probability
dc.subjectStatistical Mechanics
dc.subjectPhysics and Society
dc.titleMaximizing Modularity is hard
dc.typetext

Files

Collections

arXiv