Name
Abstract | ||
|---|---|---|
One of the most popular graph drawing methods is based on achieving graph-theoretic target distances. This method was used by Kamada and Kawai [15], who formulated it as an energy optimization problem. Their energy is known in the multidimensional scaling (MDS) community as the stress function. In this work, we show how to draw graphs by stress majorization, adapting a technique known in the MDS community for more than two decades. It appears that majorization has advantages over the technique of Kamada and Kawai in running time and stability. We also found the majorization-based optimization being essential to a few extensions to the basic energy model. These extensions can improve layout quality and computation speed in practice. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1007/978-3-540-31843-9_25 | Graph Drawing |
Keywords | Field | DocType |
stress function,computation speed,mds community,graph drawing,stress majorization,layout quality,graph-theoretic target distance,basic energy model,multidimensional scaling,energy optimization problem,majorization-based optimization,energy optimization | Conjugate gradient method,Graph drawing,Combinatorics,Mathematical optimization,Multidimensional scaling,Computer science,Force-directed graph drawing,Majorization,Stress majorization,Computation,Cholesky decomposition | Conference |
Volume | ISSN | ISBN |
3383 | 0302-9743 | 3-540-24528-6 |
Citations | PageRank | References |
146 | 6.18 | 12 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Emden R. Gansner | 1 | 1117 | 115.32 |
| Yehuda Koren | 2 | 9090 | 484.08 |
| Stephen North | 3 | 442 | 19.56 |