On account of the enormous amounts of rules that can be produced by data mining algorithms, knowledge post-processing is a difficult stage in an association rule discovery process....
Julien Blanchard, Bruno Pinaud, Pascale Kuntz, Fab...
Knowledge Discovery in time series usually requires symbolic time series. Many discretization methods that convert numeric time series to symbolic time series ignore the temporal ...
We describe an application of relational knowledge discovery to a key regulatory mission of the National Association of Securities Dealers (NASD). NASD is the world's largest...
With an increasing use of data mining tools and techniques, we envision that a Knowledge Discovery and Data Mining System (KDDMS) will have to support and optimize for the followi...
The quest to nd models usefully characterizing data is a process central to the scienti c method, and has been carried out on many fronts. Researchers from an expanding number of ...