HotPeriods: Visual Correlation Analysis of Interval Data
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With the ever increasing amount and complexity of data, visual correlation analysis is a fundamental tool to find correlations and relationships in the data. Most of the previous techniques (e.g., scatter plots or heat maps) focus on point data, i.e., data with point measures, such as prices or volumes. In this demo paper, we focus on data with interval measures, that is data where measures consist of an interval or range of values, such as price ranges or time intervals. We present a tool, termed HOTPERIODS, which allows to visualize correlations for two interval measures in the two-dimensional space. Two interval measures represent a rectangle in the two-dimensional space. To visualize such data, we first perform a rectangle aggregation. The result of this aggregation is a density matrix, where each cell stores the number of rectangles covering the corresponding point in space. For the visualization of the density matrix, color-coding is used to represent different values similar to heat maps. We will illustrate the usefulness of HOTPERIODS for the analysis of stock market data and tourism data, both of which show interval measures.
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