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A Flexible Approach for Visual Data Mining
January-March 2002 (vol. 8 no. 1)
pp. 39-51

Abstract—The exploration of heterogenous information spaces requires suitable mining methods as well as effective visual interfaces. Most of the existing systems concentrate either on mining algorithms or on visualization techniques. This paper describes a flexible framework for Visual Data Mining which combines analytical and visual methods to achieve a better understanding of the information space. We provide several preprocessing methods for unstructured information spaces such as a flexible hierarchy generation with user controlled refinement. Moreover, we develop new visualization techniques including an intuitive Focus+Context technique to visualize complex hierarchical graphs. A special feature of our system is a new paradigm for visualizing information structures within their frame of reference.

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Index Terms:
Information visualization, multidimenisional information modeling, hierarchies, focus+context techniques, clustering, maps, information analysis.
Citation:
Matthias Kreuseler, Heidrun Schumann, "A Flexible Approach for Visual Data Mining," IEEE Transactions on Visualization and Computer Graphics, vol. 8, no. 1, pp. 39-51, Jan.-March 2002, doi:10.1109/2945.981850
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