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A review of data mining techniques

Sang Jun Lee (University of Nebraska‐Lincoln, Lincoln, Nebraska, USA)
Keng Siau (University of Nebraska‐Lincoln, Lincoln, Nebraska, USA)

Industrial Management & Data Systems

ISSN: 0263-5577

Article publication date: 1 February 2001

15181

Abstract

Terabytes of data are generated everyday in many organizations. To extract hidden predictive information from large volumes of data, data mining (DM) techniques are needed. Organizations are starting to realize the importance of data mining in their strategic planning and successful application of DM techniques can be an enormous payoff for the organizations. This paper discusses the requirements and challenges of DM, and describes major DM techniques such as statistics, artificial intelligence, decision tree approach, genetic algorithm, and visualization.

Keywords

Citation

Jun Lee, S. and Siau, K. (2001), "A review of data mining techniques", Industrial Management & Data Systems, Vol. 101 No. 1, pp. 41-46. https://doi.org/10.1108/02635570110365989

Publisher

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MCB UP Ltd

Copyright © 2001, MCB UP Limited

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