Enabling decision trend analysis with interactive scatter plot matrices visualization

Wen Bo Wang, Mao Lin Huang, Quang Vinh Nguyen, Tony Huang, Kang Zhang, Tze-Haw Huang

    Research output: Contribution to journalArticlepeer-review

    6 Citations (Scopus)

    Abstract

    This paper presents a new interactive scatter plot visualization for multi-dimensional data analysis. We apply Rough Set Theory (RST) to reduce the visual complexity through dimensionality reduction. We use an innovative point-to-region mouse click concept to enable direct interactions with scatter points that are theoretically impossible. To show the decision trend we use a virtual Z dimension to display a set of linear flows showing approximation of the decision trend. We conducted case studies to demonstrate the effectiveness and usefulness of our new technique for analyzing the property of three popular data sets including wine quality, wages and cars. The paper also includes a pilot usability study to evaluate parallel coordinate visualization with scatter plot matrices visualization with RST results.
    Original languageEnglish
    Pages (from-to)13-23
    Number of pages11
    JournalJournal of Visual Languages and Computing
    Volume33
    DOIs
    Publication statusPublished - 2016

    Keywords

    • data analysis
    • rough sets
    • visualization

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