Optimising fuzzy description logic reasoners with general concept inclusion absorption

General Concept Inclusion (GCI) absorption algorithms have shown to play an important role in classical Description Logic (DL) reasoners. They allow to transform GCIs into simpler forms to which we may apply specialised inference rules, returning important performance gains. In this work, we develop the first absorption algorithm for fuzzy DLs, implement it in the fuzzyDL reasoner and evaluate it extensively over both classical and fuzzy ontologies. The results show that our algorithm improves the performance of the reasoner significantly.