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An HSV-Based Visual Analytic System for Data Science on Music and Beyond
Abstract
In the current era of big data, high volumes of a wide variety of valuable data—which may be of different veracities—can be easily generated or collected at a high speed in various real-life applications related to art, culture, design, engineering, mathematics, science, and technology. A data science solution helps manage, analyze, and mine these big data—such as musical data—for the discovery of interesting information and useful knowledge. As “a picture is worth a thousand words,” a visual representation provided by the data science solution helps visualize the big data and comprehend the mined information and discovered knowledge. This journal article presents a visual analytic system—which uses a hue-saturation-value (HSV) color model to represent big data—for data science on musical data and beyond (e.g., other types of big data).
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