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Granulation Based Approximate Ontologies Capture

机译:基于粒度的近似本体捕获

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摘要

Ontologies are of vital importance to the successful realization of semantic Web. Currently, the existing concepts in ontologies are not approximate but clear. However, in real application domains many concepts are difficult to define explicitly. In order to fulfill semantic Web, it's not only necessary but also important to study approximate concepts and approximate ontologies generated from the approximate concepts. In this paper, based on the principle of granular computing, a granulation model for representing approximate ontologies was constructed. Then algorithms for capturing approximate concepts and generating approximate ontologies were proposed and illustrated with a real example.
机译:本体对于成功实现语义Web至关重要。当前,本体中的现有概念不是近似的,而是清晰的。但是,在实际的应用程序域中,很难明确定义许多概念。为了实现语义Web,研究近似概念和从近似概念生成的近似本体不仅是必要的,而且是重要的。本文基于粒度计算的原理,构建了一种表示近似本体的粒度模型。然后提出了捕获近似概念并生成近似本体的算法,并通过一个实际示例进行了说明。

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