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Formal Semantics-Preserving Translation from Fuzzy ER Model to Fuzzy OWL DL Ontology

机译:从模糊ER模型到模糊猫头鹰DL本体的正式语义保留翻译

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How to quickly and cheaply construct Web ontologies has become a key technology to enable the Semantic Web. However, information imprecision and uncertainty exist in many real-world applications. Thus constructing fuzzy ontology by extracting domain knowledge from fuzzy database model such as fuzzy ER model can profitably support fuzzy ontology development. In this paper, firstly, we give the formal definition and semantics of fuzzy ER model. Then, we introduce a kind of fuzzy extension of OWL DL, named fuzzy OWL DL. Furthermore, based on the fuzzy OWL DL, the formal definition and Model-Theoretic semantics of fuzzy OWL DL ontology are given. What’s more, we realize the formal translation from fuzzy ER model to fuzzy OWL DL ontology by a semantics-preserving translation algorithm. Finally, since a fuzzy OWL DL ontology is being equivalent to a description logic f-SHOIN(D) knowledge base, the reasoning problem of satisfiability, subsumption, and redundancy of fuzzy ER model may reason automatically through reasoning mechanism of f-SHOIN(D) is also investigated, which can contribute to constructing fuzzy OWL DL ontologys exactly that meet application’s needs.
机译:如何快速和便宜构建Web本体已成为启用语义网络的关键技术。然而,许多现实世界应用中存在信息不精确和不确定性。从模糊数据库模型中提取模糊数据库模型的域知识构建模糊本体,可以盈利地支持模糊本体论。在本文中,首先,我们给出了模糊模型的形式定义和语义。然后,我们介绍了一种猫头鹰DL的模糊延伸,名为Fuzzy OWL DL。此外,基于模糊猫头鹰DL,给出了模糊猫头鹰DL本体的形式定义和模型 - 理论语义。更重要的是,通过语义保护翻译算法,实现了从模糊ER模型到模糊OWL DL本体的正式翻译。最后,由于模糊猫头鹰DL本体等同于描述逻辑F-shoin(d)知识库,因此通过F-shoin的推理机制自动推理的可满足性,增容和冗余的推理问题(D)(D. )也调查了,这可以有助于构建模糊OWL DL Ontologys,符合应用程序的需求。

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