Reasoning in a Knowledge Base (KB) is one of the most important applications of Description Logic (DL) reasoners. The execution time and storage space requirements are both significant factors that directly influence the performance of a reasoning algorithm. In this paper, we investigate a new technique for optimizing DL reasoning in order to minimize the above two factors as much as possible. This technique is applied to speed up TBox and ABox reasoning, especially for large TBoxes. The incorporation of this technique with previous optimization techniques in current DL systems can effectively solve intractable inferences. Our technique is called "overlap ontology decomposition", in which the decomposition of a given ontology into many sub-ontologies is implemented such that the semantics and inference services of the original ontology are preserved. We are concerned about how to reason effectively with multiple KBs and how to improve the efficiency of reasoning over component ontologies.
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