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DIS-C: conceptual distance in ontologies, a graph-based approach

机译:DIS-C:本体中的概念距离,基于图形的方法

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This paper presents the DIS-C approach, which is a novel method to assess the conceptual distance between concepts within an ontology. DIS-C is graph based in the sense that the whole topology of the ontology is considered when computing the weight of the relationships between concepts. The methodology is composed of two main steps. First, in order to take advantage of previous knowledge, an expert of the ontology domain assigns initial weight values to each of the relations in the ontology. Then, an automatic method for computing the conceptual relations refines the weights assigned to each relation until reaching a stable state. We introduce a metric called generality that is defined in order to evaluate the accessibility of each concept, considering the ontology like a strongly connected graph. Unlike most previous approaches, the DIS-C algorithm computes similarity between concepts in ontologies that are not necessarily represented in a hierarchical or taxonomic structure. So, DIS-C is capable of incorporating a wide variety of relationships between concepts such as meronymy, antonymy, functionality and causality.
机译:本文介绍了DIS-C方法,这是一种评估本体内概念之间概念距离的新方法。基于概念之间考虑本体的整体拓扑结构,DIS-C是图形的。方法由两个主要步骤组成。首先,为了利用以前的知识,本体域的专家为本体中的每个关系分配初始重量值。然后,用于计算概念关系的自动方法将分配给每个关系的权重,直到达到稳定状态。我们介绍了一个称为一般性的度量,以便评估每个概念的可访问性,考虑如强烈连接的图形。与大多数先前的方法不同,DIS-C算法在本体中不一定地以分类或分类结构表示的概念之间计算相似性。因此,DIS-C能够结合各种各样的关系,例如孟喻,反义,功能和因果关系。

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