Evolving SQL queries for data mining

Majid SALIM; Xin YAO

doi:10.1007/3-540-45675-9_11

Evolving SQL queries for data mining

Majid SALIM, Xin YAO

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review

6 Citations (Scopus)

Abstract

This paper presents a methodology for applying the principles of evolutionary computation to knowledge discovery in databases by evolving SQL queries that describe datasets. In our system, the fittest queries are rewarded by having their attributes being given a higher probability of surviving in subsequent queries. The advantages of using SQL queries include their readability for non-experts and ease of integration with existing databases. The evolutionary algorithm (EA) used in our system is very different from existing EAs, but seems to be effective and efficient according to the experiments to date with three different testing data sets. © Springer-Verlag Berlin Heidelberg 2002.

Original language	English
Title of host publication	Intelligent Data Engineering and Automated Learning : IDEAL 2002 : Third International Conference, Manchester, UK, August 12-14 Proceedings
Editors	Hujun YIN, Nigel ALLINSON, Richard FREEMAN, John KEANE, Simon HUBBARD
Publisher	Springer Berlin Heidelberg
Pages	62-67
Number of pages	6
ISBN (Electronic)	9783540456759
ISBN (Print)	9783540440253
DOIs	https://doi.org/10.1007/3-540-45675-9_11
Publication status	Published - 2002
Externally published	Yes
Event	3rd International Conference on Intelligent Data Engineering and Automated Learning - Manchester, United Kingdom Duration: 12 Aug 2002 → 14 Aug 2002

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer, Berlin, Heidelberg
Volume	2412
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	3rd International Conference on Intelligent Data Engineering and Automated Learning
Abbreviated title	IDEAL'02
Country/Territory	United Kingdom
City	Manchester
Period	12/08/02 → 14/08/02

Keywords

Data Mining
Evolutionary Algorithm
Genetic Programming
Evolutionary Computation
Credit Card Fraud

Access to Document

10.1007/3-540-45675-9_11

Cite this

SALIM, M., & YAO, X. (2002). Evolving SQL queries for data mining. In H. YIN, N. ALLINSON, R. FREEMAN, J. KEANE, & S. HUBBARD (Eds.), Intelligent Data Engineering and Automated Learning : IDEAL 2002 : Third International Conference, Manchester, UK, August 12-14 Proceedings (pp. 62-67). (Lecture Notes in Computer Science; Vol. 2412). Springer Berlin Heidelberg. https://doi.org/10.1007/3-540-45675-9_11

SALIM, Majid ; YAO, Xin. / Evolving SQL queries for data mining. Intelligent Data Engineering and Automated Learning : IDEAL 2002 : Third International Conference, Manchester, UK, August 12-14 Proceedings. editor / Hujun YIN ; Nigel ALLINSON ; Richard FREEMAN ; John KEANE ; Simon HUBBARD. Springer Berlin Heidelberg, 2002. pp. 62-67 (Lecture Notes in Computer Science).

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abstract = "This paper presents a methodology for applying the principles of evolutionary computation to knowledge discovery in databases by evolving SQL queries that describe datasets. In our system, the fittest queries are rewarded by having their attributes being given a higher probability of surviving in subsequent queries. The advantages of using SQL queries include their readability for non-experts and ease of integration with existing databases. The evolutionary algorithm (EA) used in our system is very different from existing EAs, but seems to be effective and efficient according to the experiments to date with three different testing data sets. {\textcopyright} Springer-Verlag Berlin Heidelberg 2002.",

keywords = "Data Mining, Evolutionary Algorithm, Genetic Programming, Evolutionary Computation, Credit Card Fraud",

author = "Majid SALIM and Xin YAO",

year = "2002",

doi = "10.1007/3-540-45675-9_11",

language = "English",

isbn = "9783540440253",

series = "Lecture Notes in Computer Science",

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editor = "Hujun YIN and Nigel ALLINSON and Richard FREEMAN and John KEANE and Simon HUBBARD",

booktitle = "Intelligent Data Engineering and Automated Learning : IDEAL 2002 : Third International Conference, Manchester, UK, August 12-14 Proceedings",

note = "3rd International Conference on Intelligent Data Engineering and Automated Learning, IDEAL'02 ; Conference date: 12-08-2002 Through 14-08-2002",

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SALIM, M & YAO, X 2002, Evolving SQL queries for data mining. in H YIN, N ALLINSON, R FREEMAN, J KEANE & S HUBBARD (eds), Intelligent Data Engineering and Automated Learning : IDEAL 2002 : Third International Conference, Manchester, UK, August 12-14 Proceedings. Lecture Notes in Computer Science, vol. 2412, Springer Berlin Heidelberg, pp. 62-67, 3rd International Conference on Intelligent Data Engineering and Automated Learning, Manchester, United Kingdom, 12/08/02. https://doi.org/10.1007/3-540-45675-9_11

Evolving SQL queries for data mining. / SALIM, Majid; YAO, Xin.
Intelligent Data Engineering and Automated Learning : IDEAL 2002 : Third International Conference, Manchester, UK, August 12-14 Proceedings. ed. / Hujun YIN; Nigel ALLINSON; Richard FREEMAN; John KEANE; Simon HUBBARD. Springer Berlin Heidelberg, 2002. p. 62-67 (Lecture Notes in Computer Science; Vol. 2412).

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review

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AU - YAO, Xin

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AB - This paper presents a methodology for applying the principles of evolutionary computation to knowledge discovery in databases by evolving SQL queries that describe datasets. In our system, the fittest queries are rewarded by having their attributes being given a higher probability of surviving in subsequent queries. The advantages of using SQL queries include their readability for non-experts and ease of integration with existing databases. The evolutionary algorithm (EA) used in our system is very different from existing EAs, but seems to be effective and efficient according to the experiments to date with three different testing data sets. © Springer-Verlag Berlin Heidelberg 2002.

KW - Data Mining

KW - Evolutionary Algorithm

KW - Genetic Programming

KW - Evolutionary Computation

KW - Credit Card Fraud

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M3 - Conference paper (refereed)

SN - 9783540440253

T3 - Lecture Notes in Computer Science

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BT - Intelligent Data Engineering and Automated Learning : IDEAL 2002 : Third International Conference, Manchester, UK, August 12-14 Proceedings

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A2 - HUBBARD, Simon

PB - Springer Berlin Heidelberg

T2 - 3rd International Conference on Intelligent Data Engineering and Automated Learning

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ER -

Evolving SQL queries for data mining

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