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Efficient TBox Reasoning with Value Restrictions—Introducing the FL_ower Reasoner

机译:具有值限制的高效TBox推理-FL_ower推理机的介绍

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The Description Logic (DL) FL_0 uses universal quantification, whereas its well-known counter-part EL uses the existential one. While for EL deciding subsumption in the presence of general TBoxes is tractable, this is no the case for FL_0. We present a novel algorithm for solving the ExpTime-hard subsumption problem in FL_0 w.r.t. general TBoxes, which is based on the computation of so-called least functional models. To build a such a model our algorithm treats TBox axioms as rules that are applied to objects of the interpretation domain. This algorithm is implemented in the FL_0wer reasoner, which uses a variant of the Rete pattern matching algorithm to find applicable rules. We present an evaluation of FL_0wer on a large set of TBoxes generated from real world ontologies. The experimental results indicate that our prototype implementation of the specialised technique for FL_0 leads in most cases to a huge performance gain in comparison to the highly-optimised tableau reasoners.
机译:描述逻辑(DL)FL_0使用通用量化,而其众所周知的对应EL使用存在量化。尽管对于EL来说,在存在通用TBox的情况下决定是否包含是很容易的,但对于FL_0却不是这样。我们提出了一种新颖的算法来解决FL_0 w.r.t中的ExpTime-hard包含问题。通用的TBoxes,它基于所谓的最小功能模型的计算。为了构建这样的模型,我们的算法将TBox公理视为适用于解释域对象的规则。该算法在FL_0wer推理机中实现,该推理机使用Rete模式匹配算法的变体来找到适用的规则。我们对来自现实世界本体的大量TBox进行FL_0wer评估。实验结果表明,与高度优化的表格推理器相比,在大多数情况下,我们针对FL_0的专用技术的原型实现可带来巨大的性能提升。

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