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Authors: Hoa Nguyen 1 and Paul Rosen 2

Affiliations: 1 University of Utah, United States ; 2 University of South Florida, United States

ISBN: 978-989-758-175-5

Keyword(s): Correlation, Correlation Visualization, Statistical Visualization.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; General Data Visualization ; Information and Scientific Visualization

Abstract: Correlation is a powerful relationship measure used in science, engineering, and business to estimate trends and make forecasts. Visualization methods, such as scatterplots and parallel coordinates, are designed to be general, supporting many visualization tasks, including identifying correlation. However, due to their generality, they do not provide the most efficient interface, in terms of speed and accuracy. This can be problematic when a task needs to be repeated frequently. To address this shortcoming, we propose a new correlation task-specific visualization method called Correlation Coordinate Plots (CCPs). CCPs transform data into a powerful coordinate system for estimating the direction and strength of correlation. To support multiple attributes, we propose 2 additional interfaces. The first is the Snowflake Visualization, a focus+context layout for exploring all pairwise correlations. The second enhances the basic CCP by using principal component analysis to project multiple attributes. We validate CCP performance in correlation-specific tasks through an extensive user study that shows improvement in both accuracy and speed. (More)

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Paper citation in several formats:
Nguyen H. and Rosen P. (2016). Improved Identification of Data Correlations through Correlation Coordinate Plots.In Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2016)ISBN 978-989-758-175-5, pages 60-71. DOI: 10.5220/0005717500600071

@conference{ivapp16,
author={Hoa Nguyen and Paul Rosen},
title={Improved Identification of Data Correlations through Correlation Coordinate Plots},
booktitle={Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2016)},
year={2016},
pages={60-71},
doi={10.5220/0005717500600071},
isbn={978-989-758-175-5},
}

TY - CONF

JO - Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2016)
TI - Improved Identification of Data Correlations through Correlation Coordinate Plots
SN - 978-989-758-175-5
AU - Nguyen H.
AU - Rosen P.
PY - 2016
SP - 60
EP - 71
DO - 10.5220/0005717500600071

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