The importance of KDD research finds its explanation in the fact that the data collected in various fields such as biology, finance, retail, astronomy, medicine are extremely rapidly growing, while our ability to analyze those data has not kept up proportionally. The task is obviously impossible to do manually. Selecting and reporting what is interesting . AAAI Press, Menlo Park, CA, 1996. In a second, more detailed level, we have to find the quantitative dependency, that is, the strength of the dependency, regarding some scale.
Probabilistic networks are the main representation for dependency modelling.
This task consists in discovering from data about a system the most significant changes in its future evolution as well as the main trends that will guide it. Christopher J. Matheus, Gregory Piatetsky-Shapiro, and Dwight McNeil. Selecting and Reporting What is Interesting . In Smyth Fayyad, Piatetsky-Shapiro and Uthurusamy, editors, Advances in Knowledge Discovery and Data Mining. MIT Press, 1996.