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Genetic Programming Theory and Practice X pp 1–14Cite as

Evolving SQL Queries from Examples with Developmental Genetic Programming

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Part of the book series: Genetic and Evolutionary Computation ((GEVO))

Abstract

Large databases are becoming ever more ubiquitous, as are the opportunities 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 explored only to a limited extent. In this chapter we show howdevelopmental genetic programming can automatically generate SQL queries from sets of positive and negative examples. We show that a developmental genetic programming system can produce queries that are reasonably accurate while excelling in human comprehensibility relative to the well-known C5.0 decision tree generation system.

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Notes

  1. 1.

    http://hampshire.edu/lspector/push.html.

  2. 2.

    C5.0 is available at http://rulequest.com/see5-info.html.

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Acknowledgements

We thank Gerome Miklau for advice regarding databases and the UCI Machine Learning Repository for use of the adult dataset; see http://archive.ics.uci.-edu/ml/index.html. This material is based upon work supported by the National Science Foundation under Grant No. 1017817. Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the authors and do not necessarily reflect the views of the National Science Foundation.

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Authors and Affiliations

  1. Department of Computer Science, University of Massachusetts, Amherst, MA, 01003, USA

    Thomas Helmuth & Lee Spector

  2. School of Cognitive Science, Hampshire College, Amherst, MA, 01002, USA

    Lee Spector

Authors
  1. Thomas Helmuth
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  2. Lee Spector
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Correspondence to Thomas Helmuth .

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Editors and Affiliations

  1. Center for the Study of Complex Systems, University of Michigan, West Hall 323, Ann Arbor, 48109, Michigan, USA

    Rick Riolo

  2. Evolved Analytics Europe BVBA, Vossenlaan, Beerse, 2340, Belgium

    Ekaterina Vladislavleva

  3. , Department of Biochemistry and Molecular, The Pennsylvania State University, Wartik Laboratory, University Park, 16802, Pennsylvania, USA

    Marylyn D Ritchie

  4. , Institute for Quantitative, Dartmouth Medical School, Medical Center Drive, Lebanon, 03756, New Hampshire, USA

    Jason H. Moore

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Helmuth, T., Spector, L. (2013). Evolving SQL Queries from Examples with Developmental Genetic Programming. In: Riolo, R., Vladislavleva, E., Ritchie, M., Moore, J. (eds) Genetic Programming Theory and Practice X. Genetic and Evolutionary Computation. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6846-2_1

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  • DOI: https://doi.org/10.1007/978-1-4614-6846-2_1

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