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Context Visualization for Visual Data Mining

  • Chapter
Visual Data Mining

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4404))

Abstract

Context and history visualization plays an important role in visual data mining especially in the visual exploration of large and complex data sets. The preservation of context and history information in the visualization can improve user comprehension of the exploration process as well as enhance the reusability of mining techniques and parameters to archive the desired results. This chapter presents methodology and various interactive visualization techniques supporting visual data mining in general as well as for visual preservation of context and history information. Algorithms are also described in supporting such methodology for visual data mining in real time.

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Authors and Affiliations

  1. Faculty of Information Technology, University of Technology, Sydney, PO Box 123, Broadway, NSW 2007, Australia

    Mao Lin Huang & Quang Vinh Nguyen

Authors
  1. Mao Lin Huang
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  2. Quang Vinh Nguyen
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Editor information

Simeon J. Simoff Michael H. Böhlen Arturas Mazeika

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© 2008 Springer-Verlag Berlin Heidelberg

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Huang, M.L., Nguyen, Q.V. (2008). Context Visualization for Visual Data Mining. In: Simoff, S.J., Böhlen, M.H., Mazeika, A. (eds) Visual Data Mining. Lecture Notes in Computer Science, vol 4404. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71080-6_16

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  • DOI: https://doi.org/10.1007/978-3-540-71080-6_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-71079-0

  • Online ISBN: 978-3-540-71080-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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