Mining the knowledge mine

The hot spots methodology for mining large real world databases
  • Graham J. Williams
  • Zhexue Huang
Machine Learning
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1342)


As databases grow in size and complexity the task of adding value to the wealth of data becomes difficult. Data mining has emerged as the technology to add value to enormous databases by finding new and important snippets (or nuggets) of knowledge. With large training sets, however, extremely large collections of nuggets are being extracted, leading to much “fools gold” amongst which to fossick for the real gold. Attention is now being directed towards the problem of how to better focus on the most precious nuggets. This paper presents the hot spots methodology, adopting a multi-strategy and interactive approach to help focus on the important nuggets. The methodology first performs data mining and then explores the resulting models to find the important nuggets contained therein. This approach is demonstrated in insurance and fraud applications.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • Graham J. Williams
    • 1
  • Zhexue Huang
    • 1
  1. 1.Cooperative Research Centre for Advanced Computational SystemsCSIRO Mathematical and Information SciencesCanberraAustralia

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