Optimised classification for taxonomic knowledge bases
Dmitry Tsarkov, Ian Horrocks · Research Explorer (The University of Manchester) · 2005
Many legacy ontologies are now being translated into Description Logic (DL) based ontology languages in order to take advantage of DL based tools and reasoning services. The resulting DL Knowledge Bases (KBs) are typically of large size, but have a very simple structure, i.e., they consist mainly of shallow taxonomies. The classification algorithms used in state-of-the-art DL reasoners may not deal well with such KBs In this paper we propose an optimisation which dramatically speeds-up classification for such KBs. 1