CLOSED SET BASED DISCOVERY OF MAXIMAL COVERING RULES
Marzena Kryszkiewicz · International Journal of Uncertainty Fuzziness and Knowledge-Based Systems · 2003
Many knowledge discovery tasks consist in mining databases. Nevertheless, there are cases in which a user is not allowed to access the database and can deal only with a provided fraction of knowledge. Still, the user hopes to find new interesting relationships. Surprisingly, a small number of patterns can be augmented into new knowledge so considerably that its analysis may become infeasible. In the article, we offer a method of inferring the concise lossless and sound representation of association rules in the form of maximal covering rules from a concise lossless representation of all derivable patterns. The respective algorithm is offered as well.