Semantic Forgetting in Expressive Description Logics

Forgetting is an important ontology extraction technology. We present a semantic forgetting method for ALC ontologies. The method forgets concept names, and captures the semantic content over the remaining vocabulary of an ontology, possibly, by introducing helper concept symbols. In an evaluation, the method performed well on large-scale ontologies when forgetting 10-50% of the vocabulary and the number of helper symbols occurring in the extracts decreased as the number of forgetting symbols increased. Against the forgetting tool Fame(Q), good performance was achieved while more semantic content was preserved.