The proposed approach is composed of two main parts (as
shown in Fig. 3). First, the knowledge base allows
formalizing user knowledge and goals. Domain knowledge
offers a general view over user knowledge in database
domain, and user expectations express the prior user
knowledge over the discovered rules. Second, the postprocessing
task consists in applying iteratively a set of filters
over extracted rules in order to extract interesting rules:
minimum improvement constraint filter, item-relatedness
filter, rule schema filters/pruning