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Cited by 1,633

The DOI matches its Crossref record; 53 of the 53 references it cites were found in a registry or an index.

Information visualization and visual data mining

Open access
Keim, D.A.·2002·IEEE Transactions on Visualization and Computer Graphics
DOI 10.1109/2945.981847
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Abstract

Never before in history has data been generated at such high volumes as it is today. Exploring and analyzing the vast volumes of data is becoming increasingly difficult. Information visualization and visual data mining can help to deal with the flood of information. The advantage of visual data exploration is that the user is directly involved in the data mining process. There are a large number of information visualization techniques which have been developed over the last decade to support the exploration of large data sets. In this paper, we propose a classification of information visualization and visual data mining techniques which is based on the data type to be visualized, the visualization technique, and the interaction and distortion technique. We exemplify the classification using a few examples, most of them referring to techniques and systems presented in this special section.

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Citations

Cites

Show all 53 references

Research works printed but not linked: 23

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  2. Ware, 2000, Information Visualization: Perception for Design
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  5. Lopez, 2002, A Scalable Framework for Information Visualization, IEEE Trans. Visualization and Computer Graphics, 8, 39
  6. Battista, 1999, Graph Drawing
  7. Huber, 1985, The Annals of Statistics, Projection Pursuit, 13, 435
  8. 10.2307/1390897 · doi:10.2307/1390897
  9. Spence, Visualization for Functional Design, 4
  10. 10.1109/VISUAL.1993.398859 · doi:10.1109/visual.1993.398859
  11. 10.1109/ICSMC.1988.754351 · doi:10.1109/icsmc.1988.754351
  12. 10.1109/VISUAL.1991.175795 · doi:10.1109/visual.1991.175795
  13. 10.2307/1390754 · DOI
  14. Tierney, 1991, Lispstat: An Object-Orientated Environment for Statistical Computing and Dynamic Graphics
  15. 10.1109/VISUAL.1993.398863 · doi:10.1109/visual.1993.398863
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  18. Anupam, Dataspace: 3D Visualization of Large Databases, 82
  19. Schaffer, Comparing Fisheye and Full-Zoom Techniques for Navigation of Hierarchically Clustered Networks, 87
  20. Carpendale, 1997, IEEE Computer Graphics and Applications, special issue on information visualization, 17, 42
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  23. Wilhelm, Software for Interactive Statistical GraphicsA Review

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Metadata

Authors
Keim, D. A.
Venue
IEEE Transactions on Visualization and Computer Graphics
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2002
Volume
8
Issue
1
Pages
1-8
ISSN
1077-2626 (ISSN-L)
DOI
10.1109/2945.981847
OpenAlex
W2151530263
Cited by
1,633
References
53
FWCI
38.94
Type
journal article
Language
en
Open access
green
Licence
ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html (vor)

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Keim, D. A. (2002). Information visualization and visual data mining. IEEE Transactions on Visualization and Computer Graphics. https://doi.org/10.1109/2945.981847

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