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We introduce optimization techniques for reasoning in DL^N – a recently introduced family of nonmonotonic description logics whose characterizing features appear well-suited to model the examples naturally arising in biomedical domains and semantic web access control policies. Such optimizations are validated experimentally on large KBs with more than 30K axioms. Speedups exceed 1 order of magnitude. For the first time, response times compatible with real-time reasoning are obtained with nonmonotonic KBs of this size
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