Accelerated Force Computation for Physics-Based Information Visualization
dc.contributor.author | Hao, Ming C. | en_US |
dc.contributor.author | Dayal, Umeshwar | en_US |
dc.contributor.author | Cotting, Daniel | en_US |
dc.contributor.author | Holenstein, Thomas | en_US |
dc.contributor.author | Gross, Markus | en_US |
dc.contributor.editor | G.-P. Bonneau and S. Hahmann and C. D. Hansen | en_US |
dc.date.accessioned | 2014-01-30T07:36:31Z | |
dc.date.available | 2014-01-30T07:36:31Z | |
dc.date.issued | 2003 | en_US |
dc.description.abstract | Visualization of similarity is an emerging technique for analyzing relation-based data sets. A common way of computing the respective layouts in an information space is to employ a physics-based mass-spring system. Force computation, however, is costly and of order N2. In this paper, we propose a new acceleration method to adopt a well-known optimized force-computation algorithm which drastically reduces the computation time to the order of N log N. The basic idea is to derive a two-pass, "prediction and correction" procedure including a customized potential function. We have applied this method to two different applications: web access and sales analysis. Both demonstrate the efficiency and versatility of the presented method. | en_US |
dc.description.seriesinformation | Eurographics / IEEE VGTC Symposium on Visualization | en_US |
dc.identifier.isbn | 3-905673-01-0 | en_US |
dc.identifier.issn | 1727-5296 | en_US |
dc.identifier.uri | https://doi.org/10.2312/VisSym/VisSym03/059-066 | en_US |
dc.publisher | The Eurographics Association | en_US |
dc.title | Accelerated Force Computation for Physics-Based Information Visualization | en_US |
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