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Reasoning within expressive fuzzy rough description logics

机译：表达性模糊粗糙描述逻辑中的推理

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摘要

It is generally accepted that the management of imprecision and vagueness will yield more intelligent and realistic knowledge-based applications. Description Logics (DLs) are suitable, well-known logics for managing structured knowledge that have gained considerable attention the last decade. The current research progress and the existing problems of uncertain or imprecise knowledge representation and reasoning in DLs are analyzed in this paper. An integration between the theories of fuzzy DLs and rough DLs has been attempted by providing fuzzy rough DLs based on fuzzy rough set theory. The syntax, semantics and properties of fuzzy rough DLs are given. It is proved that the satisfiability, subsumption, entailment and ABox consistency reasoning in fuzzy rough DLs may be reduced to the ABox consistency reasoning in the corresponding fuzzy DLs.
机译：人们普遍认为，对不精确性和模糊性的管理将产生更加智能和现实的基于知识的应用程序。描述逻辑（DL）是用于管理结构化知识的合适的，众所周知的逻辑，在过去的十年中已经引起了广泛的关注。分析了数字图书馆中知识表示和推理的不确定性或不精确性的研究现状和存在的问题。通过基于模糊粗糙集理论提供模糊粗糙DL，尝试将模糊DL和粗糙DL的理论进行整合。给出了模糊粗糙DL的语法，语义和性质。实践证明，模糊粗糙DL中的可满足性，包含性，蕴含性和ABox一致性推理可以降低为相应模糊DL中的ABox一致性推理。

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