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A String Metric for Ontology Alignment

机译:本体对齐的字符串指标

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摘要

Ontologies are today a key part of every knowledge based system. They provide a source of shared and precisely defined terms, resulting in system interoperability by knowledge sharing and reuse. Unfortunately, the variety of ways that a domain can be conceptualized results in the creation of different ontologies with contradicting or overlapping parts. For this reason ontologies need to be brought into mutual agreement (aligned). One important method for ontology alignment is the comparison of class and property names of ontologies using string-distance metrics. Today quite a lot of such metrics exist in literature. But all of them have been initially developed for different applications and fields, resulting in poor performance when applied in this new domain. In the current paper we present a new string metric for the comparison of names which performs better on the process of ontology alignment as well as to many other field matching problems.
机译:今天,本体是每个基于知识的系统的关键部分。它们提供了共享且精确定义的术语的来源,从而通过知识共享和重用实现了系统的互操作性。不幸的是,领域可以被概念化的多种方式导致创建了具有矛盾或重叠部分的不同本体。因此,本体必须达成共识(一致)。本体对齐的一种重要方法是使用字符串距离度量比较本体的类名和属性名。如今,文献中存在大量此类指标。但是所有这些工具最初都是为不同的应用程序和领域开发的,因此在此新领域中应用时,导致性能不佳。在当前的论文中,我们提出了一种用于名称比较的新字符串度量,该度量在本体对齐过程以及许多其他字段匹配问题上表现更好。

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