Data Mining Techniques in Clustering, Association and Classification

  • Dawn E. Holmes
  • Jeffrey Tweedale
  • Lakhmi C. Jain
Part of the Intelligent Systems Reference Library book series (ISRL, volume 23)

Abstract

The term Data Mining grew from the relentless growth of techniques used to interrogation masses of data. As a myriad of databases emanated from disparate industries, management insisted their information officers develop methodology to exploit the knowledge held in their repositories. The process of extracting this knowledge evolved as an interdisciplinary field of computer science within academia. This included study into statistics, database management and Artificial Intelligence (AI). Science and technology provide the stimulus for an extremely rapid transformation from data acquisition to enterprise knowledge management systems.

Keywords

Data Mining Association Rule Data Mining Technique Text Cluster Rich Attribute 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Dawn E. Holmes
    • 1
  • Jeffrey Tweedale
    • 2
  • Lakhmi C. Jain
    • 2
  1. 1.Department of Statistics and Applied ProbabilityUniversity of California Santa BarbaraSanta BarbaraUSA
  2. 2.School of Electrical and Information EngineeringUniversity of South AustraliaAdelaideAustralia

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