Visual Data Mining with ILOG Discovery

  • Thomas Baudel
  • Bruno Haible
  • Georg Sander
Conference paper

DOI: 10.1007/978-3-540-24595-7_51

Part of the Lecture Notes in Computer Science book series (LNCS, volume 2912)
Cite this paper as:
Baudel T., Haible B., Sander G. (2004) Visual Data Mining with ILOG Discovery. In: Liotta G. (eds) Graph Drawing. GD 2003. Lecture Notes in Computer Science, vol 2912. Springer, Berlin, Heidelberg

Abstract

Data mining deals with the discovery of useful and previously unknown knowledge from large data sets [3]. Traditional data mining tools use a combination of machine learning, statistical analysis, modeling techniques and database technology to find patterns, exceptions and subtle relationships in data. Typical applications include market segmentation, customer profiling, fraud detection, credit risk analysis, and business data development.

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Thomas Baudel
    • 1
  • Bruno Haible
    • 1
  • Georg Sander
    • 1
  1. 1.ILOG SAGentilly CedexFRANCE

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