Quantification and granulation

Data mining holds the promise of extracting unsuspected information from very large databases: Methods have been developed to build association rules from categorical data. However, often many fine grained rules are generated. Additionally, much real data is not only categorical; it is quantitative. In forming association rules, quantitative values are often reduced to categorical values; this may overly simplify results. The concern of the work presented is considering how fine grained rules might be aggregated and the role that noncategorical data might have. It appears that soft computing techniques may be useful