An automated approach for the optimization of pixel-based visualizations

During the last two decades, a wide variety of advanced methods for the visual exploration of large data sets have been proposed. For most of these techniques user interaction has become a crucial element, since there are many situations in which users or analysts have to select the right parameter settings from among many in order to construct insightful visualizations. The right choice of input parameters is essential, since suboptimal parameter settings or the investigation of irrelevant data dimensions make the exploration process more time consuming and may result in wrong conclusions. But finding the right parameters is often a tedious process and it becomes almost impossible for an analyst to find an optimal parameter setting manually because of the volume and complexity of today's data sets. Therefore, we propose a novel approach for automatically determining meaningful parameter- and attribute settings based on the combined analysis of the data space and the resulting vi...

• Type: Journal
• Year: 2007
• Where: IVS
• Authors: Jörn Schneidewind, Mike Sips, Daniel A. Keim
• Keywords: IVS 2007, Parameter, Parameter Settings, Right Parameters