We propose a new method for mining frequent patterns in a language that
combines both Semantic Web ontologies and rules. In particular we consider the
setting of using a language that combines description logics with DL-safe
rules. This setting is important for the practical application of data mining
to the Semantic Web. We focus on the relation of the semantics of the
representation formalism to the task of frequent pattern discovery, and for the
core of our method, we propose an algorithm that exploits the semantics of the
combined knowledge base.