Association rules mining with categories and regular expressions based pruning

We present an extended version of the well known Apriori algorithm used for mining association rules. Its novelty consists in employing regular expressions in order to specify the form of the rules intended to be generated. These are further used for pruning in the rule generation step, thus speeding up the process. We show that the new version of the algorithm was used for generating medical hypotheses for some problems in the field without risking to loose generality.