A flexible approach for visual data mining

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 comb...

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Veröffentlicht in:IEEE transactions on visualization and computer graphics Jg. 8; H. 1; S. 39 - 51
Hauptverfasser: Kreuseler, M., Schumann, H.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.01.2002
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Algorithm design and analysis
Algorithms
Computer graphics
Data mining
Data visualization
Exploration
Hierarchies
Information analysis
Mathematical analysis
Merging
Mining
Pattern analysis
Pattern recognition
Statistical analysis
Visual
Visualization
Warehousing
ISSN:1077-2626, 1941-0506
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Zusammenfassung: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 pre-processing 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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ISSN:1077-2626
1941-0506
DOI:10.1109/2945.981850