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
For the problem of Modularity Clustering, first introduced by Newman and Girvan in 2004, we are give...
National audienceNetworks are often used to represent complex systems arising in a variety of fields...
National audienceNetworks are often used to represent complex systems arising in a variety of fields...
Modularity is a recently introduced quality measure for graph clusterings. It has immediately ...
Modularity is a recently introduced quality measure for graph clusterings. It has immediately receiv...
Modularity is a recently introduced quality measure for graph clusterings. It has immediately receiv...
The maximum modularity of a graph is a parameter widely used to describe the level of clustering or ...
Abstract — Modularity is a recently introduced quality measure for graph clusterings. It has immedia...
Modularity is a recently introduced quality measure for graph clusterings. It has immediately receiv...
International audienceHeuristics are widely applied to modularity maximization models for the identi...
International audienceHeuristics are widely applied to modularity maximization models for the identi...
The maximum modularity of a graph is a parameter widely used to describe the level of clustering or ...
International audienceWe present a new graph clustering algorithm aimed at obtaining clusterings of ...
International audienceClustering is a central problem in machine learning for which graph-based appr...
Modularity is a quality function on partitions of a network which may be used to identify highly clu...
For the problem of Modularity Clustering, first introduced by Newman and Girvan in 2004, we are give...
National audienceNetworks are often used to represent complex systems arising in a variety of fields...
National audienceNetworks are often used to represent complex systems arising in a variety of fields...
Modularity is a recently introduced quality measure for graph clusterings. It has immediately ...
Modularity is a recently introduced quality measure for graph clusterings. It has immediately receiv...
Modularity is a recently introduced quality measure for graph clusterings. It has immediately receiv...
The maximum modularity of a graph is a parameter widely used to describe the level of clustering or ...
Abstract — Modularity is a recently introduced quality measure for graph clusterings. It has immedia...
Modularity is a recently introduced quality measure for graph clusterings. It has immediately receiv...
International audienceHeuristics are widely applied to modularity maximization models for the identi...
International audienceHeuristics are widely applied to modularity maximization models for the identi...
The maximum modularity of a graph is a parameter widely used to describe the level of clustering or ...
International audienceWe present a new graph clustering algorithm aimed at obtaining clusterings of ...
International audienceClustering is a central problem in machine learning for which graph-based appr...
Modularity is a quality function on partitions of a network which may be used to identify highly clu...
For the problem of Modularity Clustering, first introduced by Newman and Girvan in 2004, we are give...
National audienceNetworks are often used to represent complex systems arising in a variety of fields...
National audienceNetworks are often used to represent complex systems arising in a variety of fields...