On the Suitability of Genetic-Based Algorithms for Data Mining

Sunil Choenni

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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 languageEnglish
Title of host publicationAdvances in Database Technologies
Subtitle of host publicationER ’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
EditorsYahiko Kambayashi, Dik Lun Lee, Ee-Peng Lim, Mukesh Kumar Mohania, Yoshifumi Masunaga
Place of PublicationBerlin, Heidelberg
PublisherSpringer
Pages55-67
ISBN (Electronic)978-3-540-49121-7
ISBN (Print)978-3-540-65690-6
DOIs
Publication statusPublished - 1998
Event1st International Workshop on Data Warehousing and Data Mining, DWDM 1998 - Singapore, Singapore
Duration: 19 Nov 199820 Nov 1998
Conference number: 1

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume1552
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Workshop

Workshop1st International Workshop on Data Warehousing and Data Mining, DWDM 1998
Abbreviated titleDWDM
CountrySingapore
CitySingapore
Period19/11/9820/11/98

Keywords

  • DB-DM: DATA MINING

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