Knowledge Discovery in Databases (KDD): Difference between revisions
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== References == | == References == | ||
*[De Martino et al., 2002] M. De Martino, A. Bertone, R. Albertoni, H. Hauska, U. Demsar, M. Dunkars. Technical Report of Data Mining, INVISIP IST-2000-29640, Information Visualisation for Site Planning, WP No2: Technology Analysis, D2.2, 28.2.2002 | *[De Martino et al., 2002] M. De Martino, A. Bertone, R. Albertoni, H. Hauska, U. Demsar, M. Dunkars. Technical Report of Data Mining, INVISIP IST-2000-29640, Information Visualisation for Site Planning, WP No2: Technology Analysis, D2.2, 28.2.2002 | ||
[[Category:Glossary]] | |||
Revision as of 07:29, 28 August 2006
KDD refers to the overall process of discovering useful knowledge from data. [De Martino et al., 2002]
KDD is an integration of multiple technologies for data management such as database management and data warehousing, statistic machine learning, decision support, and others such as visualisation and parallel computing.
[De Martino et al., 2002]
References
- [De Martino et al., 2002] M. De Martino, A. Bertone, R. Albertoni, H. Hauska, U. Demsar, M. Dunkars. Technical Report of Data Mining, INVISIP IST-2000-29640, Information Visualisation for Site Planning, WP No2: Technology Analysis, D2.2, 28.2.2002