We introduce an energy model whose minimum energy drawings reveal the clusters of the drawn graph. Here a cluster is a set of nodes with many internal edges and few edges to nodes outside the set. The drawings of the best-known force and energy models do not clearly show clusters for graphs whose diameter is small relative to the number of nodes. We formally characterize the minimum energy drawings of our energy model. This characterization shows in what sense the drawings separate clusters, and how the distance of separated clusters to the other nodes can be interpreted
Image analysis, pattern recognition, and computer vision pose very interesting and challenging probl...
Abstract. Cluster discovery is an essential part of many data mining applications. While cluster dis...
Abstract. A promising approach to graph clustering is based on the intuitive notion of intra-cluster...
We introduce an energy model whose minimum energy drawings reveal the clusters of the drawn graph. H...
In many real-world graphs, like social networks, hyperlink structures, and software dependency graph...
We discuss several criteria for clustering graphs, and identify two criteria which are not biased t...
National audienceGraphs are mathematical structures that provide natural means for complex-data r...
A promising approach to graph clustering is based on the intuitive notion of intracluster density ve...
By dividing potential energy landscapes into basins of attractions surrounding minima and linking th...
Graph drawing is the pictorial representation of graphs in a multi-dimensional space. Energy models ...
We have developed a novel algorithm for cluster analysis that is based on graph theoretic techniques...
In this paper we present an analytical model for per-formance evaluation of a clustered sensor netwo...
Current graph drawing algorithms enable the creation of two dimensional node-link diagrams of huge g...
Disconnectivity graphs are used to characterize the potential energy surfaces of Lennard-Jones clust...
We develop a framework for the image segmentation problem based on a new graph-theoretic formulation...
Image analysis, pattern recognition, and computer vision pose very interesting and challenging probl...
Abstract. Cluster discovery is an essential part of many data mining applications. While cluster dis...
Abstract. A promising approach to graph clustering is based on the intuitive notion of intra-cluster...
We introduce an energy model whose minimum energy drawings reveal the clusters of the drawn graph. H...
In many real-world graphs, like social networks, hyperlink structures, and software dependency graph...
We discuss several criteria for clustering graphs, and identify two criteria which are not biased t...
National audienceGraphs are mathematical structures that provide natural means for complex-data r...
A promising approach to graph clustering is based on the intuitive notion of intracluster density ve...
By dividing potential energy landscapes into basins of attractions surrounding minima and linking th...
Graph drawing is the pictorial representation of graphs in a multi-dimensional space. Energy models ...
We have developed a novel algorithm for cluster analysis that is based on graph theoretic techniques...
In this paper we present an analytical model for per-formance evaluation of a clustered sensor netwo...
Current graph drawing algorithms enable the creation of two dimensional node-link diagrams of huge g...
Disconnectivity graphs are used to characterize the potential energy surfaces of Lennard-Jones clust...
We develop a framework for the image segmentation problem based on a new graph-theoretic formulation...
Image analysis, pattern recognition, and computer vision pose very interesting and challenging probl...
Abstract. Cluster discovery is an essential part of many data mining applications. While cluster dis...
Abstract. A promising approach to graph clustering is based on the intuitive notion of intra-cluster...