ATOM:自动目标驱动的本体合并

Salvatore Raunich, E. Rahm
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引用次数: 76

摘要

许多领域中本体和分类法的激增日益要求集成多个这样的本体,以提供对它们的统一视图。我们演示了一种新的自动方法来合并大型分类法,如产品目录或web目录。我们的方法是基于源分类法和目标分类法之间的等价匹配来合并它们。它是目标驱动的,也就是说,它尽可能地保留目标分类法的结构。此外,我们还展示了该方法如何利用源和目标概念之间的附加关系在语义上改进合并结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ATOM: Automatic target-driven ontology merging
The proliferation of ontologies and taxonomies in many domains increasingly demands the integration of multiple such ontologies to provide a unified view on them. We demonstrate a new automatic approach to merge large taxonomies such as product catalogs or web directories. Our approach is based on an equivalence matching between a source and target taxonomy to merge them. It is target-driven, i.e. it preserves the structure of the target taxonomy as much as possible. Further, we show how the approach can utilize additional relationships between source and target concepts to semantically improve the merge result.
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