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• W2398277981 abstract "Reasoning in very expressive Description Logics (DLs) such as SROIQ is often hard since non-determinism, e.g., from disjunctions or cardinality restrictions, requires a case-by-case analysis and since a strict separation between intensional (TBox) and extensional (ABox) knowledge is not possible due to nominals. Current state-of-the-art reasoners for SROIQ are typically based on (hyper-)tableau algorithms, where higher level reasoning tasks such as classification are reduced to possibly many consistency tests. For large ABoxes and more expressive DLs, reasoning then easily becomes infeasible since the ABox has to be considered in each test. For less expressive DLs, optimisations have been proposed that allow for considering only parts of the ABox for checking whether an individual is an instance of a specific concept [22,23]. It is, however, not clear how these optimisations can be extended to SROIQ. Furthermore, approaches based on partitioning and modularisation require a syntactic pre-analysis of the concepts, roles, and individuals in a KB, which can be quite costly for more expressive DLs and, due to the static analysis, only queries with specific concepts are supported. Rewriting axioms such that ABox reasoning is improved also carries the risk that this negatively influences other reasoning tasks for which ABox reasoning is potentially not or less relevant. Another possibility is the caching of the completion graph that is built by the tableau algorithm during the initial consistency check. The re-use of (parts of) the cached completion graph in subsequent tests reduces the number of consequences that have to be re-derived for the individuals of the ABox. Existing approaches based on this idea (e.g., [17]) are, however, not very suitable for handling non-determinism. Since caching and re-using non-deterministically derived facts can easily cause unsound consequences, the non-deterministically derived facts are usually simply discarded and re-derived if necessary. We address this and present a technique that allows for identifying nondeterministic facts that can safely be re-used. The approach is based on a set of conditions that can be checked locally and, thus, allows for efficiently identifying individuals step-by-step for which non-deterministic consequences have to be re-considered in subsequent tests. The presented technique can directly be integrated into existing tableaubased reasoning systems without significant adaptations and reduces reasoning effort for all tasks for which consequences from the ABox are potentially relevant. Moreover," @default.
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• W2398277981 date "2015-01-01" @default.
• W2398277981 modified "2023-09-26" @default.
• W2398277981 title "Completion Graph Caching for Expressive Description Logics." @default.
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