Community detection consists of grouping related vertices that usually show high intra-cluster connectivity and low inter-cluster connectivity. This is an important feature that many networks exhibit and detecting such communities can be challenging, especially when they are densely connected. The method we propose is a degenerate agglomerative hierarchical clustering algorithm (DAHCA) that aims at finding a community structure in networks. We tested this method using common classes of graph benchmarks and compared it to some state-of-the-art community detection algorithms
This article presents an efficient hierarchical clustering algo-rithm that solves the problem of cor...
The study of complex networks has significantly advanced our understanding of community structures w...
Clustering of social networks, known as community detection is a fundamental partof social network a...
Community detection consists of grouping related vertices that usually show high intra-cluster conne...
Community detection is a highly active research area that aims to identify groups of vertices with s...
International audienceDue to the development and popularization of Internet, there is more and more ...
Social networks usually display a hierarchy of communities and it is the task of community detection...
Community structures are an important feature of many social, biological, and technological networks...
National audienceThe analysis of networks and in particular the identification of communities, or cl...
Agglomerative clustering is a well established strategy for identifying communities in networks. Com...
Social Networks generally present a hierarchy of communities. To determine these communities and the...
Vertices in a real-world social network can be grouped into densely connected communities that are s...
Community structure is one of the most fundamental and important topology characteristics of complex...
This paper introduces a hierarchical clustering algorithm in networks based upon a first divisive st...
Agglomerative Clustering techniques work by recursively merging graph vertices into communities, to ...
This article presents an efficient hierarchical clustering algo-rithm that solves the problem of cor...
The study of complex networks has significantly advanced our understanding of community structures w...
Clustering of social networks, known as community detection is a fundamental partof social network a...
Community detection consists of grouping related vertices that usually show high intra-cluster conne...
Community detection is a highly active research area that aims to identify groups of vertices with s...
International audienceDue to the development and popularization of Internet, there is more and more ...
Social networks usually display a hierarchy of communities and it is the task of community detection...
Community structures are an important feature of many social, biological, and technological networks...
National audienceThe analysis of networks and in particular the identification of communities, or cl...
Agglomerative clustering is a well established strategy for identifying communities in networks. Com...
Social Networks generally present a hierarchy of communities. To determine these communities and the...
Vertices in a real-world social network can be grouped into densely connected communities that are s...
Community structure is one of the most fundamental and important topology characteristics of complex...
This paper introduces a hierarchical clustering algorithm in networks based upon a first divisive st...
Agglomerative Clustering techniques work by recursively merging graph vertices into communities, to ...
This article presents an efficient hierarchical clustering algo-rithm that solves the problem of cor...
The study of complex networks has significantly advanced our understanding of community structures w...
Clustering of social networks, known as community detection is a fundamental partof social network a...