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International Symposium on Methodologies for Intelligent Systems

ISMIS 1996: Foundations of Intelligent Systems pp 56–67Cite as

Data mining and knowledge discovery in business databases

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1079))

Abstract

The rapid and constant growth of databases in business, government, and science has far outpaced our ability to interpret and make sense of this data avalanche, creating a need for a new generation of tools and techniques for intelligent and automated database analysis. These tools and techniques are the subject of the rapidly emerging field of data mining and knowledge discovery in databases (KDD). This paper surveys the state of the art in this field, with a particular focus on the issues and challenges in applying KDD to business databases.

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Authors and Affiliations

  1. GTE Laboratories, MS 45, 40 Sylvan Road, 02154, Waltham, MA, USA

    Gregory Piatetsky-Shapiro

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  1. Gregory Piatetsky-Shapiro
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Editor information

Zbigniew W. Raś Maciek Michalewicz

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© 1996 Springer-Verlag Berlin Heidelberg

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Piatetsky-Shapiro, G. (1996). Data mining and knowledge discovery in business databases. In: Raś, Z.W., Michalewicz, M. (eds) Foundations of Intelligent Systems. ISMIS 1996. Lecture Notes in Computer Science, vol 1079. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61286-6_131

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  • DOI: https://doi.org/10.1007/3-540-61286-6_131

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-61286-5

  • Online ISBN: 978-3-540-68440-4

  • eBook Packages: Springer Book Archive

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