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On partitioning-based optimisations in expressive fuzzy Description Logics

机译:论富有富有富有富有的基于分区的优化描述逻辑

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Fuzzy Description Logics (DLs) are a formalism for the representation of structured knowledge affected by imprecision or vagueness. A key factor in the practical success of fuzzy DLs is the availability of highly implemented reasoners. This paper studies two optimisation techniques (ABox partitioning based on individual groups and optimisation problem partitioning) in the setting of the fuzzy ontology reasoner fuzzy DL. We study the applicability of these techniques in expressive fuzzy DL languages, proposing a new strategy, and perform an empirical evaluation proving that they are not helpful in practice so far.
机译:模糊描述逻辑(DLS)是由不精确或模糊性影响的结构化知识表示的形式主义。模糊DLS实际成功的关键因素是高度实施的推理员的可用性。本文在模糊本体理发师模糊DL的设置中研究了两种优化技术(基于各个组的优化问题分配和优化问题分区)。我们在表达模糊DL语言中研究了这些技术的适用性,提出了一种新的策略,并履行了证明他们在迄今为止的实践中没有帮助。

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