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From the Art of KDD to the Science of KDD

  • Y. Kodratoff
Conference paper
Part of the International Centre for Mechanical Sciences book series (CISM, volume 382)

Abstract

It has been already largely proven that Knowledge Discovery in Databases (KDD) is an interesting new research field, able to provide financial returns to the companies that are willing to invest into it. This fact demonstrates the excellent social value of KDD. A Science, however, is not uniquely defined by this feature. It needs also to show an internal logic, due to a specific approach to the real-life problems it deals with. This last point of view has been less emphasized in the existing KDD literature. This paper attempts, without any pretense to be exhaustive, to start filling up this gap. We shall explain why KDD is not just “a bunch of techniques” but a real Science, certainly one still under organization, but which shows the strong inner motivation that other Sciences do. In conclusion we shall give a compact definition of KDD, and show what is the concept it provides measurement of, as a function of which other concepts.

Keywords

Data Mining Knowledge Discovery Knowledge Acquisition Unsupervised Learning Inductive Logic Programming 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Wien 1997

Authors and Affiliations

  • Y. Kodratoff
    • 1
  1. 1.University of Paris-SudOrsayFrance

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