The design and analysis of spatial data structures
The design and analysis of spatial data structures
Computational geometry in C (2nd ed.)
Computational geometry in C (2nd ed.)
Graph Drawing: Algorithms for the Visualization of Graphs
Graph Drawing: Algorithms for the Visualization of Graphs
Visual Exploration of Complex Time-Varying Graphs
IEEE Transactions on Visualization and Computer Graphics
Node overlap removal in clustered directed acyclic graphs
Journal of Visual Languages and Computing
GIScience'06 Proceedings of the 4th international conference on Geographic Information Science
DigitalTree: a tool for displaying biological data in tree structure
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part II
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Force-directed graph drawing algorithms are a popular method of drawing graphs, but poor scalability makes them unsuitable for drawing large graphs. The FADE paradigm uses the proximity information in recursive space decompositions to address this problem and that of high visual complexity. The FADE paradigm has been presented with a simple and common recursive space decomposition known as the quadtree. However, quadtrees have the disadvantage of not being robust with respect to small perturbations and some transformations of the input data, and this can adversely affect the resultant graph drawing. This paper investigates the FADE paradigm using an alternative recursive space decomposition known as the recursive voronoi diagram, which avoids some of the problems found in quadtrees at an additional time complexity cost. Preliminary results with random graphs and graphs in the domain of software engineering are presented and suggest that using better recursive space decompositions has promise, but the additional computational effort may not be easily justified.