Semantics oriented association rules

Abstract

It is well known that relational theory carries very little semantic. To mine deeper semantics, additional modeling are necessary. In fact, some "pure" association rules are found exist even in a randomly generated data. In this paper, we consider the relational database in which every attribute value has some additional information, such as price, fuzzy degree, neighborhood, or security compartment and levels. Two types of additions are considered: one is structure added, the other is valued-added. Somewhat a surprise, the additional cost in semantics checking is found very well compensated by the pruning of non-semantic rules.