Fast interactive visualization for multivariate data exploration

Authors:
Changhyun Lee;Wei Zhuo;Jaegul Choo;Duen Horng (Polo) Chau;Haesun Park
Affiliations:
Georgia Institute of Technology, Atlanta, Georgia, USA;Georgia Institute of Technology, Atlanta, GA, USA;Georgia Institute of Technology, Atlanta, GA, USA;Georgia Institute of Technology, Atlanta, Georgia, USA;Georgia Institute of Technology, Atlanta, GA, USA
Venue:
CHI '13 Extended Abstracts on Human Factors in Computing Systems
Year:
2013

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Abstract

We are investigating a fast layout method for visualizing and exploring relationships between multivariate data items. We improve on existing works that use the force-directed layout, which has high running time and cannot scale up for large-scale visual analysis. Our method, based on Mean Value Coordinates, has a closed-form solution that can determine items' locations in a single iteration. In addition, it has a fast running time that is linear in the number of items. We are also exploring multiple interactive visualization techniques to help users make sense of the data, such as blending multiple heat maps to simultaneously express multiple types of data distributions; and techniques to create topics, and to merge or split topics in real time.