On the Suitability of Genetic-Based Algorithms for Data Mining

Sunil Choenni

doi:10.1007/978-3-540-49121-7_5

On the Suitability of Genetic-Based Algorithms for Data Mining

Sunil Choenni

Databases (Former)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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Abstract

Data mining has as goal to extract knowledge from large databases. A database may be considered as a search space consisting of an enormous number of elements, and a mining algorithm as a search strategy. In general, an exhaustive search of the space is infeasible. Therefore, efficient search strategies are of vital importance. Search strategies on genetic-based algorithms have been applied successfully in a wide range of applications. We focus on the suitability of genetic-based algorithms for data mining. We discuss the design and implementation of a genetic-based algorithm for data mining and illustrate its potentials.

Original language	English
Title of host publication	Advances in Database Technologies
Subtitle of host publication	ER ’98 Workshops on Data Warehousing and Data Mining, Mobile Data Access, and Collaborative Work Support and Spatio-Temporal Data Management Singapore, November 19–20, 1998 Proceedings
Editors	Yahiko Kambayashi, Dik Lun Lee, Ee-Peng Lim, Mukesh Kumar Mohania, Yoshifumi Masunaga
Place of Publication	Berlin, Heidelberg
Publisher	Springer
Pages	55-67
ISBN (Electronic)	978-3-540-49121-7
ISBN (Print)	978-3-540-65690-6
DOIs	https://doi.org/10.1007/978-3-540-49121-7_5
Publication status	Published - 1998
Event	1st International Workshop on Data Warehousing and Data Mining, DWDM 1998 - Singapore, Singapore Duration: 19 Nov 1998 → 20 Nov 1998 Conference number: 1

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer
Volume	1552
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Workshop

Workshop	1st International Workshop on Data Warehousing and Data Mining, DWDM 1998
Abbreviated title	DWDM
Country/Territory	Singapore
City	Singapore
Period	19/11/98 → 20/11/98

Keywords

DB-DM: DATA MINING

Access to Document

10.1007/978-3-540-49121-7_5

On the Suitability of Genetic-Based Algorithms for Data Mining
Choenni, R. S. (Keynote speaker)
18 Nov 1998
Activity: Talk or presentation › Oral presentation

Cite this

Choenni, S. (1998). On the Suitability of Genetic-Based Algorithms for Data Mining. In Y. Kambayashi, D. L. Lee, E.-P. Lim, M. Kumar Mohania, & Y. Masunaga (Eds.), Advances in Database Technologies: ER ’98 Workshops on Data Warehousing and Data Mining, Mobile Data Access, and Collaborative Work Support and Spatio-Temporal Data Management Singapore, November 19–20, 1998 Proceedings (pp. 55-67). (Lecture Notes in Computer Science; Vol. 1552). Springer. https://doi.org/10.1007/978-3-540-49121-7_5

Choenni, Sunil. / On the Suitability of Genetic-Based Algorithms for Data Mining. Advances in Database Technologies: ER ’98 Workshops on Data Warehousing and Data Mining, Mobile Data Access, and Collaborative Work Support and Spatio-Temporal Data Management Singapore, November 19–20, 1998 Proceedings. editor / Yahiko Kambayashi ; Dik Lun Lee ; Ee-Peng Lim ; Mukesh Kumar Mohania ; Yoshifumi Masunaga. Berlin, Heidelberg : Springer, 1998. pp. 55-67 (Lecture Notes in Computer Science).

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title = "On the Suitability of Genetic-Based Algorithms for Data Mining",

abstract = "Data mining has as goal to extract knowledge from large databases. A database may be considered as a search space consisting of an enormous number of elements, and a mining algorithm as a search strategy. In general, an exhaustive search of the space is infeasible. Therefore, efficient search strategies are of vital importance. Search strategies on genetic-based algorithms have been applied successfully in a wide range of applications. We focus on the suitability of genetic-based algorithms for data mining. We discuss the design and implementation of a genetic-based algorithm for data mining and illustrate its potentials.",

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author = "Sunil Choenni",

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language = "English",

isbn = "978-3-540-65690-6",

series = "Lecture Notes in Computer Science",

publisher = "Springer",

pages = "55--67",

editor = "Yahiko Kambayashi and Lee, {Dik Lun} and Ee-Peng Lim and {Kumar Mohania}, Mukesh and Yoshifumi Masunaga",

booktitle = "Advances in Database Technologies",

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note = "1st International Workshop on Data Warehousing and Data Mining, DWDM 1998, DWDM ; Conference date: 19-11-1998 Through 20-11-1998",

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Choenni, S 1998, On the Suitability of Genetic-Based Algorithms for Data Mining. in Y Kambayashi, DL Lee, E-P Lim, M Kumar Mohania & Y Masunaga (eds), Advances in Database Technologies: ER ’98 Workshops on Data Warehousing and Data Mining, Mobile Data Access, and Collaborative Work Support and Spatio-Temporal Data Management Singapore, November 19–20, 1998 Proceedings. Lecture Notes in Computer Science, vol. 1552, Springer, Berlin, Heidelberg, pp. 55-67, 1st International Workshop on Data Warehousing and Data Mining, DWDM 1998, Singapore, Singapore, 19/11/98. https://doi.org/10.1007/978-3-540-49121-7_5

On the Suitability of Genetic-Based Algorithms for Data Mining. / Choenni, Sunil.
Advances in Database Technologies: ER ’98 Workshops on Data Warehousing and Data Mining, Mobile Data Access, and Collaborative Work Support and Spatio-Temporal Data Management Singapore, November 19–20, 1998 Proceedings. ed. / Yahiko Kambayashi; Dik Lun Lee; Ee-Peng Lim; Mukesh Kumar Mohania; Yoshifumi Masunaga. Berlin, Heidelberg: Springer, 1998. p. 55-67 (Lecture Notes in Computer Science; Vol. 1552).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - On the Suitability of Genetic-Based Algorithms for Data Mining

AU - Choenni, Sunil

N1 - Conference code: 1

PY - 1998

Y1 - 1998

N2 - Data mining has as goal to extract knowledge from large databases. A database may be considered as a search space consisting of an enormous number of elements, and a mining algorithm as a search strategy. In general, an exhaustive search of the space is infeasible. Therefore, efficient search strategies are of vital importance. Search strategies on genetic-based algorithms have been applied successfully in a wide range of applications. We focus on the suitability of genetic-based algorithms for data mining. We discuss the design and implementation of a genetic-based algorithm for data mining and illustrate its potentials.

AB - Data mining has as goal to extract knowledge from large databases. A database may be considered as a search space consisting of an enormous number of elements, and a mining algorithm as a search strategy. In general, an exhaustive search of the space is infeasible. Therefore, efficient search strategies are of vital importance. Search strategies on genetic-based algorithms have been applied successfully in a wide range of applications. We focus on the suitability of genetic-based algorithms for data mining. We discuss the design and implementation of a genetic-based algorithm for data mining and illustrate its potentials.

KW - DB-DM: DATA MINING

U2 - 10.1007/978-3-540-49121-7_5

DO - 10.1007/978-3-540-49121-7_5

M3 - Conference contribution

SN - 978-3-540-65690-6

T3 - Lecture Notes in Computer Science

SP - 55

EP - 67

BT - Advances in Database Technologies

A2 - Kambayashi, Yahiko

A2 - Lee, Dik Lun

A2 - Lim, Ee-Peng

A2 - Kumar Mohania, Mukesh

A2 - Masunaga, Yoshifumi

PB - Springer

CY - Berlin, Heidelberg

T2 - 1st International Workshop on Data Warehousing and Data Mining, DWDM 1998

Y2 - 19 November 1998 through 20 November 1998

ER -

Choenni S. On the Suitability of Genetic-Based Algorithms for Data Mining. In Kambayashi Y, Lee DL, Lim EP, Kumar Mohania M, Masunaga Y, editors, Advances in Database Technologies: ER ’98 Workshops on Data Warehousing and Data Mining, Mobile Data Access, and Collaborative Work Support and Spatio-Temporal Data Management Singapore, November 19–20, 1998 Proceedings. Berlin, Heidelberg: Springer. 1998. p. 55-67. (Lecture Notes in Computer Science). doi: 10.1007/978-3-540-49121-7_5

On the Suitability of Genetic-Based Algorithms for Data Mining

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On the Suitability of Genetic-Based Algorithms for Data Mining

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