Most graph visualization techniques focus on the structure of graphs and do not offer support for dealing with node attributes and edge labels. To enable users to detect relations...
Graph drawing and visualization represent structural information ams of abstract graphs and networks. An important subset of graphs is directed acyclic graphs (DAGs). E-Spring alg...
In recent years, many networks have become available for analysis, including social networks, sensor networks, biological networks, etc. Graph clustering has shown its effectivenes...
Background: Graph theory provides a computational framework for modeling a variety of datasets including those emerging from genomics, proteomics, and chemical genetics. Networks ...
Joshua J. Forman, Paul A. Clemons, Stuart L. Schre...
Social networks collected by historians or sociologists typically have a large number of actors and edge attributes. Applying social network analysis (SNA) algorithms to these net...
Anastasia Bezerianos, Fanny Chevalier, Pierre Drag...