Publica
Hier finden Sie wissenschaftliche Publikationen aus den FraunhoferInstituten. Visual analysis of graphs with multiple connected components
 Institute of Electrical and Electronics Engineers IEEE: IEEE Symposium on Visual Analytics Science and Technology, VAST 2009 : Colocated with the annual IEEE Visualization Conference (IEEE Vis) and the IEEE Information Visualization Conference (IEEE InfoVis), 11  16 October 2009, Atlantic City, New Jersey, USA Piscataway/NJ: IEEE, 2009 ISBN: 1424452848 ISBN: 9781424452842 ISBN: 9781424452835 S.155162 
 Symposium on Visual Analytics Science and Technology (VAST) <2009, Atlantic City/NJ> 

 Englisch 
 Konferenzbeitrag 
 Fraunhofer IGD () 
 clustering; Graphical User Interface (GUI); image generation; graph; selforganizing map 
Abstract
In this paper, we present a system for the interactive visualization and exploration of graphs with many weakly connected components. The visualization of large graphs has recently received much research attention. However, specific systems for visual analysis of graph data sets consisting of many such components are rare. In our approach, we rely on graph clustering using an extensive set of topology descriptors. Specifically, we use the SelfOrganizing Map algorithm in conjunction with a useradaptable combination of graph features for clustering of graphs. It offers insight into the overall structure of the data set. The clustering output is presented in a grid containing clusters of the connected components of the input graph. Interactive feature selection and tasktailored data views allow the exploration of the whole graph space. The system provides also tools for assessment and display of cluster quality. We demonstrate the usefulness of our system by application to a shareholder structure analysis problem based on a large realworld data set. While so far our approach is applied to weighted directed graphs only, it can be used for various graph types.