Evolving SQL Queries from Examples with Developmental Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InCollection{Helmuth:2012:GPTP,

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

}

Genetic Programming entries for Thomas Helmuth Lee Spector

Citations