Abstract
Data mining, as already noted, is a component of the knowledge discovery process. It can be defined as a set of techniques that allows data analysis and exploration in order to discover significant rules or hidden models within large archives by means of an entirely or partially automated procedure (Berry, Linoff, 1997).
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The graphic representations were developed for the DBInspector project, which was financed by the EC under the Esprit programme. Partners in the project were: the Bank of Italy, Southampton University’s Parallel Applications Centre, the Centre for Information and Financing Technologies of the Universita Cattolica del Sacro Cuore of Milan (CeTIF), AIS and Trento University. The same software was used in another EC-financed project, again as a part of Esprit. In this project it is used to carry out behaviour analyses on Banca Monte dei Paschi s.p.a.’s customers, in order to spot potential clusters of customers interested in savings management. The other partners, besides the bank, are Southampton University’s Parallel Applications Centre, were CeTIF of Milan’s Catholic University and AIS.
The same software was used in another EC-financed project, again as a part of Esprit. In this project it is used to carry out behaviour analyses on Banca Monte dei Paschi s.p.a.’s customers, in order to spot potential clusters of customers interested in savings management. The other partners beside the bank are Southampton University’s Parallel Applications Centre, were CeTIF of Milan’s Catholic University and AIS.
In terms of both good construction and integration with other technologies.
This characteristic sets them apart from expert systems: as a matter of fact, in the latter the knowledge base has to be defined and inserted by an expert, while in neural networks knowledge acquisition comes from an auto-learning process based on historical data.
John Holland was the one who initially proposed them.
GAAF was developed within the ESPRIT III — PAPAGENA project, which was sponsored by the EU.
The exact definition of centroid is „vector of the averages of a multi-varied distribution.“
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© 2003 Springer-Verlag Berlin Heidelberg
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Rajola, F. (2003). Data Mining Techniques. In: Customer Relationship Management. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24718-0_6
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DOI: https://doi.org/10.1007/978-3-540-24718-0_6
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