Abstract
Nowadays there is a huge amount of data stored in real-world databases, and this amount continues to grow fast. As pointed out by [Piatetsky-Shapiro 1991], this creates both an opportunity and a need for (semi-)automatic methods that discover the knowledge “hidden” in such databases. If such knowledge discovery activity is successful, discovered knowledge can be used to improve the decision-making process of an organization.
“Computers have promised us a fountain of wisdom but delivered a flood of data.” A frustrated MIS executive
[Frawley et al. 1991, p.l]
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Freitas, A.A. (2002). Introduction. In: Data Mining and Knowledge Discovery with Evolutionary Algorithms. Natural Computing Series. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-04923-5_1
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DOI: https://doi.org/10.1007/978-3-662-04923-5_1
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