Knowledge Discovery in Databases (KDD)

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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]


KDD refers to the overall process of discovering useful knowledge from data, and data mining refers to a particular step in this process. [...] The basic problem addressed by the KDD process is one of mapping low-level data into other forms that might be more compact, more abstract, or more useful.
[Fayyad et al., 1996]


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
  • [Fayyad et al., 1996] U. Fayyad, G. P.-Shapiro, and P. Smyth. From data mining to knowledge discovery in databases. AI Magazine, 17(3):37-54, Fall 1996. http://citeseer.ist.psu.edu/fayyad96from.html