Shape-embedded-histograms for visual data mining

A Amir, R Kashi, D. A Keim, N. S Netanyahu, M Wawryniuk

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Scatterplots are widely used in exploratory data analysis and class visualization. The advantages of scatterplots are that they are easy to understand and allow the user to draw conclusions about the attributes which span the projection screen. Unfortunately, scatterplots have the overplotting problem which is especially critical when high-dimensional data are mapped to low-dimensional visualizations. Overplotting makes it hard to detect the structure in the data, such as dependencies or areas of high density. In this paper we show that by extending the concept of Pixel Validity (1) the problem of overplotting or occlusion can be avoided and (2) the user has the possibility to see information about an additional third variable. In our extension of the Pixel Validity concept, we summarize the data which are projected onto a given region by generating a histogram over the required attribute. This is then embedded in the visualization by a pixel-based technique.
Original languageAmerican English
Title of host publicationSixth Joint Eurographics - IEEE TCVG Symposium on Visualization
StatePublished - 2004

Bibliographical note

Place of conference:Konstanz, Germany


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