Add to ORKGNational audienceA network, or graph, G = (V,E) consists of a set of vertices V = {1, . . . , n} and a set of edges E = {1, . . . ,m} connecting vertices. One of the most studied problems in the field of complex systems is to find communities, or clusters, in networks. A community consists of a subset S of the vertices of V where inner edges connecting pairs of vertices of S are more dense than cut edges connecting vertices of S to vertices of V \S. Many criteria have been proposed to evaluate partitions of V into communities
In many networks, it is of great interest to identify communities, unusually densely knit groups of ...
From various applications, in sociology or biology for instance,complex networks exhib the remarquab...
Modularity maximization is extensively used to detect communities in complex networks. It has been s...
National audienceA network, or graph, G = (V,E) consists of a set of vertices V = {1, . . . , n} and...
International audienceCommunity detection in networks based on modularity maximization is currently ...
International audienceFinding clusters, or communities, in a graph, or network is a very important p...
International audienceHeuristics are widely applied to modularity maximization models for the identi...
National audienceNetworks are often used to represent complex systems arising in a variety of fields...
Several algorithms have been proposed to compute partitions of networks into communities that score ...
International audienceClustering is a central problem in machine learning for which graph-based appr...
We consider two new problems regarding the impact of edge addition or removal on the modularity of p...
International audienceWe propose mathematical programming based aproaches to refine graph clustering...
Agglomerative clustering is a well established strategy for identifying communities in networks. Com...
Modularity Density Maximization is a graph clustering problem which avoids the resolution limit dege...
National audienceThe analysis of networks and in particular the identification of communities, or cl...
In many networks, it is of great interest to identify communities, unusually densely knit groups of ...
From various applications, in sociology or biology for instance,complex networks exhib the remarquab...
Modularity maximization is extensively used to detect communities in complex networks. It has been s...
National audienceA network, or graph, G = (V,E) consists of a set of vertices V = {1, . . . , n} and...
International audienceCommunity detection in networks based on modularity maximization is currently ...
International audienceFinding clusters, or communities, in a graph, or network is a very important p...
International audienceHeuristics are widely applied to modularity maximization models for the identi...
National audienceNetworks are often used to represent complex systems arising in a variety of fields...
Several algorithms have been proposed to compute partitions of networks into communities that score ...
International audienceClustering is a central problem in machine learning for which graph-based appr...
We consider two new problems regarding the impact of edge addition or removal on the modularity of p...
International audienceWe propose mathematical programming based aproaches to refine graph clustering...
Agglomerative clustering is a well established strategy for identifying communities in networks. Com...
Modularity Density Maximization is a graph clustering problem which avoids the resolution limit dege...
National audienceThe analysis of networks and in particular the identification of communities, or cl...
In many networks, it is of great interest to identify communities, unusually densely knit groups of ...
From various applications, in sociology or biology for instance,complex networks exhib the remarquab...
Modularity maximization is extensively used to detect communities in complex networks. It has been s...