Visualization of high-density 3D graphs using nonlinear visual space transformations

Ming C. Hao; Umeshwar Dayal; Pankaj Garg; Vijay Machiraju

doi:10.1117/12.458795

12 March 2002 Visualization of high-density 3D graphs using nonlinear visual space transformations

Ming C. Hao, Umeshwar Dayal, Pankaj Garg, Vijay Machiraju

Proceedings Volume 4665, Visualization and Data Analysis 2002; (2002) https://doi.org/10.1117/12.458795
Event: Electronic Imaging, 2002, San Jose, California, United States

Abstract

The real world data distribution is seldom uniform. Clutter and sparsity commonly occur in visualization. Often, clutter results in overplotting, in which certain data items are not visible because other data items occlude them. Sparsity results in the inefficient use of the available display space. Common mechanisms to overcome this include reducing the amount of information displayed or using multiple representations with a varying amount of detail. This paper describes out experiments on Non-Linear Visual Space Transformations (NLVST). NLVST encompasses several innovative techniques: (1) employing a histogram for calculating the density of data distribution; (2) mapping the raw data values to a non-linear scale for stretching a high-density area; (3) tightening the sparse area to save the display space; (4) employing different color ranges of values on a non-linear scale according to the local density. We have applied NLVST to several web applications: market basket analysis, transactions observation, and IT search behavior analysis.

Citation Download Citation

Ming C. Hao, Umeshwar Dayal, Pankaj Garg, and Vijay Machiraju "Visualization of high-density 3D graphs using nonlinear visual space transformations", Proc. SPIE 4665, Visualization and Data Analysis 2002, (12 March 2002); https://doi.org/10.1117/12.458795

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