XMAP:一种新的结构化方法,用于对齐OWL-Full本体

W. Djeddi, M. Khadir
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引用次数: 23

摘要

一方面,由于本体开发社区之间的概念和习惯差异,在两个本体之间自动生成对应关系非常困难。另一方面,对齐困难随着所涉及数据的数量和体积呈指数级增长。这项工作提出了一个对齐算法的命题;该方法的独创性在于考虑到对齐的上下文,以克服包含相似类的大型本体的问题。除此之外,我们还提出了一种自动学习如何结合语言和结构亲和力的方法。除了sigmoid函数外,还使用加权和,该函数必须根据语言亲和度的权重进行移位,以拟合我们的输入范围[0到1]。最后,将所提出的算法实现为Protege插件,并应用于对描述汽轮机的本体进行对齐。在性能和预校准工作方面,分析了与手动校准相比的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
XMAP: A novel structural approach for alignment of OWL-Full ontologies
Automatic correspondence generation between two ontologies, is of great difficulty due, on one hand, to conceptual and habit differences between ontology development communities. On the other hand, alignment difficulties grew exponentially with the number and volume of the involved data. This work presents a proposition of an alignment algorithm; where the approach originality consists in taking into account the context of the alignment in order to overcome the problem of large size ontologies containing similar classes. Adding to that, we present an automatic approach to learn how to combine the linguistic and structural affinity. The weighted, sum in addition to the sigmoid function, which has to be shifted according to the weight of the linguistic affinity and to fit our input range of [0 to 1] is also used: Finally, the proposed algorithm is implemented as a Protege plug-in, and applied to align ontologies describing a steam turbine. Results are analyzed compared to manual alignment in terms of performances and pre-alignment efforts.
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