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http://dx.doi.org/10.3745/KTSDE.2016.5.6.261

A Guiding System of Visualization for Quantitative Bigdata Based on User Intention  

Byun, Jung Yun (단국대학교 컴퓨터학과)
Park, Young B. (단국대학교 전자계산학과)
Publication Information
KIPS Transactions on Software and Data Engineering / v.5, no.6, 2016 , pp. 261-266 More about this Journal
Abstract
Chart suggestion method provided by various existing data visualization tools makes chart recommendations without considering the user intention. Data visualization is not properly carried out and thus, unclear in some tools because they do not follow the segmented quantitative data classification policy. This paper provides a guideline that clearly classifies the quantitative input data and that effectively suggests charts based on user intention. The guideline is two-fold; the analysis guideline examines the quantitative data and the suggestion guideline recommends charts based on the input data type and the user intention. Following this guideline, we excluded charts in disagreement with the user intention and confirmed that the time user spends in the chart selection process has decreased.
Keywords
Bigdata Visualization; Open Source Visualization Tool; Visualization for Quantitative Data; Visualization Guideline; Chart Recommendation;
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