Review: Data mining techniques and applications - A decade review from 2000 to 2011

Authors:
Shu-Hsien Liao;Pei-Hui Chu;Pei-Yuan Hsiao
Affiliations:
Department of Management Sciences, Tamkang University, No. 151, Yingzhuan Rd., Tamsui Dist., New Taipei City 25137, Taiwan, ROC;Department of Management Sciences, Tamkang University, No. 151, Yingzhuan Rd., Tamsui Dist., New Taipei City 25137, Taiwan, ROC;Department of Management Sciences, Tamkang University, No. 151, Yingzhuan Rd., Tamsui Dist., New Taipei City 25137, Taiwan, ROC
Venue:
Expert Systems with Applications: An International Journal
Year:
2012

Citing 39
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A study on the applications of data mining techniques to enhance customer lifetime value

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Optimisation and data mining techniques for the screening of epileptic patients

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Public institutions' investments with data mining techniques

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Automatic abstraction in reinforcement learning using data mining techniques

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Data mining techniques for improving the reliability of system identification

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Collaborative particle swarm optimization with a data mining technique for manufacturing cell design

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Application of data mining techniques in the financial sector for profitable customer relationship management

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Constructing credit auditing and control & management model with data mining technique

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Using data mining techniques for multi-diseases prediction modeling of hypertension and hyperlipidemia by common risk factors

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Product development with data mining techniques: A case on design of digital camera

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Visitors of two types of museums: A segmentation study

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Competitive positioning and performance assessment in the construction industry

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Abstract

In order to determine how data mining techniques (DMT) and their applications have developed, during the past decade, this paper reviews data mining techniques and their applications and development, through a survey of literature and the classification of articles, from 2000 to 2011. Keyword indices and article abstracts were used to identify 216 articles concerning DMT applications, from 159 academic journals (retrieved from five online databases), this paper surveys and classifies DMT, with respect to the following three areas: knowledge types, analysis types, and architecture types, together with their applications in different research and practical domains. A discussion deals with the direction of any future developments in DMT methodologies and applications: (1) DMT is finding increasing applications in expertise orientation and the development of applications for DMT is a problem-oriented domain. (2) It is suggested that different social science methodologies, such as psychology, cognitive science and human behavior might implement DMT, as an alternative to the methodologies already on offer. (3) The ability to continually change and acquire new understanding is a driving force for the application of DMT and this will allow many new future applications.