Abstract
Data mining is concerned with the discovery of interesting patterns and models in data. In practice, data mining has become an established technology with applications in a wide range of areas that include marketing, health care, finance, environmental planning, up to applications in e-commerce and e-science. This paper presents selected data mining techniques and applications developed in the course of the SolEuNet 5FP IST project Data Mining and Decision Support for Business Competitiveness: A European Virtual Enterprise (2000–2003).
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Lavrač, N. (2006). SolEuNet: Selected Data Mining Techniques and Applications. In: Spiliopoulou, M., Kruse, R., Borgelt, C., Nürnberger, A., Gaul, W. (eds) From Data and Information Analysis to Knowledge Engineering. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-31314-1_4
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DOI: https://doi.org/10.1007/3-540-31314-1_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-31313-7
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