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SMART Software for Decision Makers KDD Experience

Oatley, G., MacIntyre, J., Ewart, B. and Mugambi, E. (2002) SMART Software for Decision Makers KDD Experience. In: Macintosh, A. and Moulton, M., (eds.) Applications and Innovations in Intelligent Systems IX. Springer-Verlag London Ltd., pp. 43-61.

Link to Published Version: http://dx.doi.org/10.1007/978-1-4471-0149-9_4
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Abstract

SMART Software for Decision Makers (SSDM) was a Department of Trade and Industry (DTI) initiative running during the period 1998-2000. The Centre for Adaptive Systems at the University of Sunderland was appointed by the DTI to run one of the two Demonstrator Clubs in the UK. The purpose of these clubs was to facilitate technology transfer between academia and industry, in the areas of fault diagnosis and prediction, intelligent control systems, and knowledge discovery in databases (KDD).

Sunderland SSDM Club decided to use the various industrial members problems and data to build a number of “mini-demonstrators”. In the KDD cluster, three demonstrator applications were developed, accompanied by supporting material and a series of seminars, which illustrated the various stages in the KDD process to all club members.

This paper describes three KDD application demonstrators, developed with data from a manufacturing company, with consultants in business clustering, and from data from a local police force, to investigate the phenomena of repeat victimization.The work involved data preprocessing, data transformation, data mining, and the development of visual tools for interpretation. With both the business clustering and police data much of the time was spent in data preparation, and so tools were developed so that the members could conduct their own data mining and interpretation experiments, lessening the need for the extraction of domain knowledge from the members.

Publication Type: Book Chapter
Publisher: Springer-Verlag London Ltd.
Copyright: © 2002 Springer- Verlag London
Other Information: ES2001, the Twenty-first SGES International Conference on Knowledge Based Systems and Applied Artificial Intelligence, Cambridge, December 2001
URI: http://researchrepository.murdoch.edu.au/id/eprint/36009
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