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Verwendung von Bildern zur Exploration und Analyse großer Datenmengen

  • Conference paper
Informatik ’98

Part of the book series: Informatik aktuell ((INFORMAT))

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Zusammenfassung

Durch den rasanten technologischen Fortschritt steigt die Menge an Daten, die in heutigen Computersystemen gespeichert ist, sehr schnell an. Damit wird die Suche nach interessanter Information innerhalb der Datenbestände immer schwieriger. In diesem Beitrag wird ein neuer Ansatz zur Datenexploration und -analyse vorgestellt, der auf neuartigen Visualisierungstechniken basiert und für die Exploration und Analyse sehr großer Datenbanken entwickelt wurde. Die prinzipielle Idee dabei ist die gleichzeitige Darstellung möglichst vieler Datenobjekte am Bildschirm, wobei jeder Datenwert durch ein Pixel des Bildschirms repräsentiert wird.

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Literatur

  1. Tufte E. R.: ‘Envisioning Information’, Graphics Press, Cheshire, CT, 1990.

    Google Scholar 

  2. Andrews D. F.: ‘Plots of High-Dimensional Data’, in: Biometrics, Vol. 29, 1972, pp. 125–136.

    Google Scholar 

  3. Cleveland W. S.: ‘Visualizing Data’, AT&T Bell Laboratories, Murray Hill, NJ, Hobart Press, Summit NJ, 1993.

    Google Scholar 

  4. Chernoff H.: ‘The Use of Faces to Represent Points in k-Dimensional Space Graphically’, Journal Amer. Statistical Association, Vol. 68, pp. 361–368.

    Google Scholar 

  5. Dunn G., Everitt B.: ‘An Introduction to Mathematical Taxonomy ’, Cambridge University Press, Cambridge, MA, 1982.

    MATH  Google Scholar 

  6. Harman H. H.: ‘Modern Factor Analysis’, University of Chicago Press, 1967.

    Google Scholar 

  7. Shepard R. N., Romney A. K., Nerlove S. B.: ‘Multidimensional Scaling’, Seminar Press, New York, 1972.

    Google Scholar 

  8. Huber P. J.: ‘Projection Pursuit’, The Annals of Statistics, Vol. 13, No. 2, 1985, pp. 435–474.

    Article  MATH  MathSciNet  Google Scholar 

  9. Asimov D.: ‘The Grand Tour: A Tool For Viewing Multidimensional Data’, SI AM Journal of Science & Stat. Comp., Vol. 6, 1985, pp. 128–143.

    Article  MATH  MathSciNet  Google Scholar 

  10. Inselberg A., Dimsdale B.: ‘Parallel Coordinates: A Tool for Visualizing Multi-Dimensional Geometry’, Visualization ’90, San Francisco, CA, 1990, pp. 361–370.

    Google Scholar 

  11. Tufte E. R.: ‘The Visual Display of Quantitative Information’, Graphics Press, Cheshire, CT, 1983.

    Google Scholar 

  12. Pickett R. M., Grinstein G. G.: ‘Iconographie Displays for Visualizing Multidimensional Data’, Proc. IEEE Conf. on Systems, Man and Cybernetics, IEEE Press, Piscataway, NJ, 1988, pp. 514–519.

    Book  Google Scholar 

  13. Beddow J.: ‘Shape Coding of Multidimensional Data on a Mircocomputer Display’, Visualization ’90, San Francisco, CA, 1990, pp. 238–246.

    Google Scholar 

  14. LeBlanc J., Ward M. O., Wittels N.: ‘Exploring N-Dimensional Databases’, Visualization’90, San Francisco, CA, 1990, pp. 230–239.

    Google Scholar 

  15. Shneiderman B.: ‘Tree Visualization with Treemaps: A 2D Space-Filling Approach’, ACM Transactions on Graphics, Vol. 11, No. 1, pp. 92–99, 1992.

    Article  MATH  Google Scholar 

  16. Becker R. A., Eick S. G., Wilks A. R.: ‘Visualizing Network Data’, Transactions on Visualization and Computer Graphics, Vol. 1, No. 1, 1995.

    Google Scholar 

  17. Hendley R. J., Drew N. S., Wood A. M., Beale R.: ‘Narcissus: Visualizing Information’, Proc. Int. Symp. on Information Visualization, Atlanta, GA, 1995, pp. 90–94.

    Google Scholar 

  18. Sarkar M., Brown M.: ‘Graphical Fisheye Views’, Communications of the ACM, Vol. 37, No. 12, 1994, pp. 73–84.

    Article  Google Scholar 

  19. Lamping J., Rao R., Pirolli P.: ‘A Focus + Context Technique Based on Hyperbolic Geometry for Visualizing Large Hierarchies’, Proc. Human Factors in Computing Systems CHI’95 Conf., Denver, CO, 1995, pp. 401–408.

    Google Scholar 

  20. Ward M. O.: ‘XmdvTool: Integrating Multiple Methods for Visualizing Multivariate Data’, Visualization’94, Washington, DC, 1994, pp. 326–336.

    Google Scholar 

  21. Bederson B.: ‘Pad++: Advances in Multiscale Interfaces’, Proc. Human Factors in Computing Systems CHI ’94 Conf., Boston, MA, 1994, p. 315.

    Book  Google Scholar 

  22. Beshers C., Feiner S.: ‘AutoVisual: Rule-Based Design of Interactive Multivariate Visualizations’, IEEE Computer Graphics and Applications, Vol. 13, No. 4, 1993, pp. 41–49.

    Article  Google Scholar 

  23. Keim D. A.: ‘Databases and Visualization’,Tutorial, Int. Conf. on Management of Data (SIG- MOD’96), 1996 (postscript file available at http://www.informatik.uni-halle.de/~keim).

    Google Scholar 

  24. Keim D. A., Kriegel H.-P., Ankerst M.: ‘Recursive Pattern: A Technique for Visualizing Very Large Amounts of Data’, Visualization ’95, Atlanta, GA, 1995, pp. 279–286.

    Book  Google Scholar 

  25. Ankerst M., Keim D. A., Kriegel H.-P.: ‘Circle-Segments: A Technique for Visually Exploring Large Multidimensional Data Sets’, Visualization ’96, Hot Topic Session, San Francisco CA, 1996.

    Google Scholar 

  26. Keim D. A., Kriegel H.-P., Seidl T.: ‘Supporting Data Mining of Large Databases by Visual Feedback Queries’, Proc. 10th Int. Conf. on Data Engineering, Houston, TX, 1994, pp. 302–313.

    Google Scholar 

  27. Keim D. A.: ‘Visual Support for Query Specification and Data Mining’, Dissertation, Ludwig-Maximilians-Universität München, 1994.

    Google Scholar 

  28. Keim D. A., Kriegel H.-P.: ‘VisDB: Database Exploration using Multidimensional Visualization’, Computer Graphics & Applications, Sept. 1994, pp. 40–49.

    Google Scholar 

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Authors and Affiliations

  1. Institut für Informatik, Martin-Luther-Universität Halle-Wittenberg, Kurt-Mothes-Str. 1, 06120, Halle (Saale), Germany

    Daniel A. Keim

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  1. Daniel A. Keim
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Editors and Affiliations

  1. Institut für Wissens- und Sprachverarbeitung Fakultät für Informatik, Otto-von-Guericke-Universität Magdeburg, Universitätsplatz 2, D-39106, Magdeburg, Germany

    Jürgen Dassow  & Rudolf Kruse  & 

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© 1998 Springer-Verlag Berlin Heidelberg

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Keim, D.A. (1998). Verwendung von Bildern zur Exploration und Analyse großer Datenmengen. In: Dassow, J., Kruse, R. (eds) Informatik ’98. Informatik aktuell. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-72283-7_3

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  • DOI: https://doi.org/10.1007/978-3-642-72283-7_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-64938-0

  • Online ISBN: 978-3-642-72283-7

  • eBook Packages: Springer Book Archive

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