Edge bundling methods became popular for visualising large dense networks; however, most of previous work mainly relies on geometry to define compatibility between the edges. In this paper, we present a new framework for edge bundling, which tightly integrates topology, geometry and importance. In particular, we introduce new edge compatibility measures, namely importance compatibility and topology compatibility. More specifically, we present four variations of force directed edge bundling method based on the framework: Centrality-based bundling, Radial bundling, Topology-based bundling, and Orthogonal bundling. Our experimental results with social networks, biological networks, geographic networks and clustered graphs indicate that our new framework can be very useful to highlight the most important topological skeletal structures of the input networks. © 2012 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Nguyen, Q., Hong, S. H., & Eades, P. (2012). TGI-EB: A new framework for edge bundling integrating topology, geometry and importance. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7034 LNCS, pp. 123–135). https://doi.org/10.1007/978-3-642-25878-7_13
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