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首页> 外文期刊>International journal on Semantic Web and information systems >Fuzzy Probabilistic Ontology Approach: A Hybrid Model for Handling Uncertain Knowledge in Ontologies
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Fuzzy Probabilistic Ontology Approach: A Hybrid Model for Handling Uncertain Knowledge in Ontologies

机译：模糊概率本体论方法：一种处理本体中不确定知识的混合模型

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摘要

In spite of the undeniable success of the ontologies, where they have been widely applied successfully to represent the knowledge in lots of real-world problems, they cannot represent and reason with uncertain knowledge which inherently appears in most domains. To cope with this issue, this article presents a new approach for dealing with rich-uncertainty domains. In fact, it is mainly based on integrating hybrid models which combine both fuzzy logic and Bayesian networks. On the other hand, the Fuzzy multi-entity Bayesian network (FzMEBN) proposed as a hybrid model which enhances the classical multi-entity Bayesian network using fuzzy logic, it can be used to represent and reason with probabilistic and vague knowledge simultaneously. Thus, as a language belongs to the proposed approach, this study proposes a promising solution to overcome the weakness of the Probabilistic Ontology Web Language (PR-OWL) based on FzMEBN to allow dealing with vague and probabilistic knowledge in ontologies. The proposed extension is evaluated with a case study in the medical field (diabetes diseases).
机译：尽管本体的不可否认的成功，他们已被广泛应用于代表大量现实问题的知识，但它们不能代表和有理由具有不确定的知识，其固有地出现在大多数域中。要应对这个问题，本文提出了一种处理富裕不确定性域的新方法。事实上，它主要基于集模糊逻辑和贝叶斯网络的整合混合模型。另一方面，建议使用模糊逻辑增强经典多实体贝叶斯网络的混合模型的模糊多实体贝叶斯网络（FZMebn），它可以用于同时用概率和模糊知识来表示和理由。因此，作为一种语言属于所提出的方法，本研究提出了一个有希望的解决方案，以克服概率基于FZMebn的概率本体网络语言（PR-OWL）的弱点，以便在本体中处理模糊和概率知识。在医疗领域（糖尿病疾病）的案例研究评估了所提出的延期。

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