Evolving SQL Queries for Data Mining

  • Majid Salim
  • Xin Yao
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2412)


This paper presents a methodology for applying the principles of evolutionary computation to knowledge discovery in databases by evolving SQL queries that describe datasets. In our system, the fittest queries are rewarded by having their attributes being given a higher probability of surviving in subsequent queries. The advantages of using SQL queries include their readability for non-experts and ease of integration with existing databases. The evolutionary algorithm (EA) used in our system is very different from existing EAs, but seems to be effective and efficient according to the experiments to date with three different testing data sets.


Data Mining Evolutionary Algorithm Genetic Programming Evolutionary Computation Credit Card Fraud 
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 Berlin Heidelberg 2002

Authors and Affiliations

  • Majid Salim
    • 1
  • Xin Yao
    • 1
  1. 1.School of Computer ScienceThe University of BirminghamEdgbastonUK

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