AIJul 16, 2015

Optimizing the computation of overriding

arXiv:1507.04630v112 citations
Originality Incremental advance
AI Analysis

This work addresses efficiency issues in nonmonotonic reasoning for biomedical and semantic web applications, representing an incremental improvement.

The paper tackles the problem of slow reasoning in nonmonotonic description logics (DLN) by introducing optimization techniques, achieving speedups exceeding 10x and enabling real-time reasoning on knowledge bases with over 30,000 axioms.

We introduce optimization techniques for reasoning in DLN---a recently introduced family of nonmonotonic description logics whose characterizing features appear well-suited to model the applicative 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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