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首页> 外文会议>International Conference on Conceptual Modeling; 20061106-09; Tucson,AZ(US) >Ontology with Likeliness and Typicality of Objects in Concepts
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Ontology with Likeliness and Typicality of Objects in Concepts

机译：概念中对象的似然性和典型性的本体论

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摘要

Ontologies play an indispensable role in the Semantic Web by specifying the definitions of concepts and individual objects. However, most of the existing methods for constructing ontologies can only specify concepts as crisp sets. However, we cannot avoid encountering concepts that are without clear boundaries, or even vague in meanings. Therefore, existing ontology models are unable to cope with many real cases effectively. With respect to a certain category, certain objects are considered as more representative or typical. Cognitive psychologists explain this by the prototype theory of concepts. This notion should also be taken into account to improve conceptual modeling. While there has been different research attempting to handle vague concepts with fuzzy set theory, formal methods for measuring typicality of objects are still insufficient. We propose a cognitive model of concepts for ontologies, which handles both likeliness (fuzzy membership grade) and typicality of individuals. We also discuss the nature and differences between likeliness and typicality. This model not only enhances the effectiveness of conceptual modeling, but also brings the results of reasoning closer to human thinking. We believe that this research is beneficial to future research on ontological engineering in the Semantic Web.
机译：通过指定概念和单个对象的定义，本体在语义网中起着不可或缺的作用。但是，大多数现有的用于构建本体的方法只能将概念指定为清晰集。但是，我们无法避免遇到没有明确界限甚至含义含糊的概念。因此，现有的本体模型无法有效地应对许多实际情况。关于某个类别，某些对象被认为更具代表性或典型性。认知心理学家通过概念原型理论对此进行了解释。还应考虑到此概念以改进概念建模。尽管已经有不同的研究试图用模糊集理论来处理模糊的概念，但是用于度量对象典型性的形式方法仍然不足。我们提出了一种本体论概念的认知模型，该模型可以处理个体的可能性（模糊成员资格等级）和典型性。我们还将讨论相似性和典型性之间的本质和差异。该模型不仅增强了概念建模的有效性，而且使推理的结果更接近于人类的思维。我们认为这项研究对语义网中本体工程的未来研究是有益的。

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