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WIREs Data Mining Knowl Discov
Impact Factor: 2.111

An overview of interactive visual data mining techniques for knowledge discovery

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In the past decade, the analysis of data has faced the challenge of dealing with very large and complex datasets and the real‐time generation of data. Technologies to store and access these complex and large datasets are in place. However, robust and scalable analysis technologies are needed to extract meaningful information from these datasets. The research field of Information Visualization and Visual Data Analytics addresses this need. Information visualization and data mining are often used complementary to each other. Their common goal is the extraction of meaningful information from complex and possibly large data. However, though data mining focuses on the usage of silicon hardware, visualization techniques also aim to access the powerful image‐processing capabilities of the human brain. This article highlights the research on data visualization and visual analytics techniques. Furthermore, we highlight existing visual analytics techniques, systems, and applications including a perspective on the field from the chemical process industry.

The process of visual analytics according to Ref .
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KinFit's polar chart implementation for displaying data with multiple dimensions, typically used for identifying optimal production process states.
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Multidimensional representation of five variables using KinFit.
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Charts used by Evonik Industries AG to display quality attributes during the production process. The chart on the bottom half of the figure is called a ChemSPFchart and the chart on the top half of the figure is a histogram.
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The figures shows a brute force SSH attacks from the Internet to computers located at the University of Konstanz. The figure has been reproduced with accordance to the Creative Commons Attribution‐ShareAlike 3.0 Unported License (http://creativecommons.org/licenses/by‐sa/3.0/deed.en_US).
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The textual tree view and magic eye view of the Coordinated Graph Visualization (CGV) system.
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The graphical user interface of the Coordinated Graph Visualization (CGV) system.
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A typical Eclipse RPC grahpical user interface taken from the KNIME data mining software.
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The knowledge discovery from data process augmented with the visual analytics process. The dashed components and lines are the augmented elements from visual analytics.
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Browse by Topic

Fundamental Concepts of Data and Knowledge > Knowledge Representation
Technologies > Visualization
Application Areas > Data Mining Software Tools

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