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Chapter 1 EVOLVING SQL QUERIES FROM EXAMPLES WITH DEVELOPMENTAL GENETIC PROGRAMMING
BibTeX
@MISC{Helmuth_chapter1,
author = {Thomas Helmuth and Lee Spector},
title = {Chapter 1 EVOLVING SQL QUERIES FROM EXAMPLES WITH DEVELOPMENTAL GENETIC PROGRAMMING},
year = {}
}
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Abstract
Large databases are becoming ever more ubiquitous, as are the op-portunities for discovering useful knowledge within them. Evolutionary computation methods such as genetic programming have previously been applied to several aspects of the problem of discovering knowledge in databases. The more specific task of producing human-comprehensible SQL queries has several potential applications but has thus far been ex-plored only to a limited extent. In this chapter we show how developmen-tal genetic programming can automatically generate SQL queries from sets of positive and negative examples. We show that a developmental ge-netic programming system can produce queries that are reasonably accu-rate while excelling in human comprehensibility relative to the well-known C5.0 decision tree generation system.
Keyphrases
genetic programming useful knowledge well-known c5 developmen-tal genetic programming human comprehensibility relative several aspect evolutionary computation method developmental ge-netic programming system limited extent specific task negative example several potential application decision tree generation system sql query human-comprehensible sql query large database
