Data mining – A review

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...

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Main Authors: LEE, S.J., SIAU, Keng
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 1998
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Online Access:https://ink.library.smu.edu.sg/sis_research/9546
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Institution: Singapore Management University
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spelling sg-smu-ink.sis_research-105462024-11-15T06:54:03Z Data mining – A review LEE, S.J. SIAU, Keng 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. 1998-11-24T08:00:00Z text https://ink.library.smu.edu.sg/sis_research/9546 Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Databases and Information Systems
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Databases and Information Systems
spellingShingle Databases and Information Systems
LEE, S.J.
SIAU, Keng
Data mining – A review
description 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.
format text
author LEE, S.J.
SIAU, Keng
author_facet LEE, S.J.
SIAU, Keng
author_sort LEE, S.J.
title Data mining – A review
title_short Data mining – A review
title_full Data mining – A review
title_fullStr Data mining – A review
title_full_unstemmed Data mining – A review
title_sort data mining – a review
publisher Institutional Knowledge at Singapore Management University
publishDate 1998
url https://ink.library.smu.edu.sg/sis_research/9546
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