We study community structure of networks. We have developed a scheme for maximizing the modularity Q based on mean field methods. Further, we have defined a simple family of random networks with community structure; we understand the behavior of these networks analytically. Using these networks, we show how the mean field methods display better performance than previously known deterministic methods for optimization of Q
In this paper, we first discuss the definition of modularity (Q) used as a metric for community qual...
Networks constitute powerful means of representing various types of complex systems, where nodes den...
Networks capture pairwise interactions between entities and are frequently used in applications such...
We study community structure of networks. We have developed a scheme for maximizing the modularity Q...
Abstract—Many networks including social networks, computer networks, and biological networks are fou...
Many real-world complex networks exhibit a community structure, in which the modules correspond to a...
Detecting community structure is fundamental to clarify the link between structure and function in c...
The detection of community structure has been used to reveal the relationships between individual o...
National audienceNetworks are often used to represent complex systems arising in a variety of fields...
International audienceHeuristics are widely applied to modularity maximization models for the identi...
The ubiquity of modular structure in real-world complex networks is being the focus of attention in ...
In many networks, it is of great interest to identify communities, unusually densely knit groups of ...
The study of network structure is pervasive in sociology, biology, computer science, and many other ...
Modular structure is ubiquitous among complex networks. To see why such networks evolve towards modu...
Abstract—Many networks, indifferent of their function and scope, converge to a scale-free architectu...
In this paper, we first discuss the definition of modularity (Q) used as a metric for community qual...
Networks constitute powerful means of representing various types of complex systems, where nodes den...
Networks capture pairwise interactions between entities and are frequently used in applications such...
We study community structure of networks. We have developed a scheme for maximizing the modularity Q...
Abstract—Many networks including social networks, computer networks, and biological networks are fou...
Many real-world complex networks exhibit a community structure, in which the modules correspond to a...
Detecting community structure is fundamental to clarify the link between structure and function in c...
The detection of community structure has been used to reveal the relationships between individual o...
National audienceNetworks are often used to represent complex systems arising in a variety of fields...
International audienceHeuristics are widely applied to modularity maximization models for the identi...
The ubiquity of modular structure in real-world complex networks is being the focus of attention in ...
In many networks, it is of great interest to identify communities, unusually densely knit groups of ...
The study of network structure is pervasive in sociology, biology, computer science, and many other ...
Modular structure is ubiquitous among complex networks. To see why such networks evolve towards modu...
Abstract—Many networks, indifferent of their function and scope, converge to a scale-free architectu...
In this paper, we first discuss the definition of modularity (Q) used as a metric for community qual...
Networks constitute powerful means of representing various types of complex systems, where nodes den...
Networks capture pairwise interactions between entities and are frequently used in applications such...