Discovering SQL Queries from Examples using Intelligent Algorithms
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gp-bibliography.bib Revision:1.8010
- @InProceedings{Martins:2018:LA-CCI,
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author = "Denis Mayr Lima Martins and Gottfried Vossen and
Fernando Buarque {de Lima Neto}",
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booktitle = "2018 IEEE Latin American Conference on Computational
Intelligence (LA-CCI)",
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title = "Discovering SQL Queries from Examples using
Intelligent Algorithms",
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year = "2018",
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abstract = "Formulating database queries in terms of SQL is often
a challenge for journalists, business administrators,
and the growing number of non-database experts that are
required to access and explore data. To alleviate this
problem, we proposed a Query By Example (QBE) approach
powered by intelligent algorithms that discovers
database queries from a few tuple examples provided by
the user. We investigated the effectiveness of three
algorithms, namely, Greedy Search, Genetic Programming,
and CART decision trees in discovering queries in two
distinct databases. To the best of our knowledge, no
other research has focused on the comparative analysis
of such algorithms in the context of QBE. Our results
show that CART decision trees were capable of
discovering the most accurate queries. However, CART
tends to produce long queries, which may hinder user
interpretation. Finally, we suggest that the use of
Interactive Evolutionary Computational Intelligence may
improve the quality of queries discovered by Genetic
Programming and may naturally incorporate diverse user
preferences in the discovery process.",
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keywords = "genetic algorithms, genetic programming, Databases,
Decision trees, Sensitivity, Sociology, Statistics,",
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DOI = "doi:10.1109/LA-CCI.2018.8625260",
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month = nov,
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notes = "Also known as \cite{8625260}",
- }
Genetic Programming entries for
Denis Mayr Lima Martins
Gottfried Vossen
Fernando Buarque de Lima Neto
Citations