Clusterwise data mining within a fuzzy querying interface

This paper, is a further development of a combined fuzzy querying and data mining paradigm. The point of departure is the FQUERY for Access. Its earlier version offered the generation of fuzzy association rules within the fuzzy querying interface. We report on extensions to a wider range of available data mining tools, mainly from cluster analysis,and more specifically, a clustering algorithm by Owsinski and Zadrozny. The data to be clustered is first fuzzified using a dictionary of linguistic terms. Additionally, the resulting clusters are helpful in running other data mining tools, notably the generation of association rules.