Accelerated Force Computation for Physics-Based Information Visualization

Hao, Ming C.; Dayal, Umeshwar; Cotting, Daniel; Holenstein, Thomas; Gross, Markus

Accelerated Force Computation for Physics-Based Information Visualization

Files

059-066.pdf (2.03 MB)

Date

2003

Authors

Hao, Ming C.
Dayal, Umeshwar
Cotting, Daniel
Holenstein, Thomas
Gross, Markus

Publisher

The Eurographics Association

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.

        @inproceedings{:10.2312/VisSym/VisSym03/059-066
,
booktitle = {Eurographics / IEEE VGTC Symposium on Visualization
},
editor = {G.-P. Bonneau and S. Hahmann and C. D. Hansen
},
title = {{Accelerated Force Computation for Physics-Based Information Visualization
}},
author = {Hao, Ming C. and 
Dayal, Umeshwar and 
Cotting, Daniel and 
Holenstein, Thomas and 
Gross, Markus
},
year = {2003
},
publisher = {The Eurographics Association
},
ISSN = {1727-5296
},
ISBN = {3-905673-01-0
},
DOI = {/10.2312/VisSym/VisSym03/059-066
}
}