Evolving SQL Queries from Examples with Developmental Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8120
- @InCollection{Helmuth:2012:GPTP,
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author = "Thomas Helmuth and Lee Spector",
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title = "Evolving SQL Queries from Examples with Developmental
Genetic Programming",
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booktitle = "Genetic Programming Theory and Practice X",
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year = "2012",
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series = "Genetic and Evolutionary Computation",
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editor = "Rick Riolo and Ekaterina Vladislavleva and
Marylyn D. Ritchie and Jason H. Moore",
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publisher = "Springer",
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chapter = "1",
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pages = "1--14",
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address = "Ann Arbor, USA",
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month = "12-14 " # may,
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keywords = "genetic algorithms, genetic programming, Data mining,
Classification, SQL, Push, PushGP",
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isbn13 = "978-1-4614-6845-5",
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URL = "http://dx.doi.org/10.1007/978-1-4614-6846-2_1",
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URL = "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.466.9078",
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URL = "http://faculty.hampshire.edu/lspector/pubs/gptp-2012-preprint.pdf",
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DOI = "doi:10.1007/978-1-4614-6846-2_1",
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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 how
developmental 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 = "part of \cite{Riolo:2012:GPTP} published after the
workshop in 2013",
- }
Genetic Programming entries for
Thomas Helmuth
Lee Spector
Citations