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A Structure-Based Similarity Spreading Approach for Ontology Matching

机译:本体匹配的基于结构的相似性传播方法

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Most of the frequently used ontology mapping methods to date are based on linguistic information implied in ontologies. However, same concepts in different ontologies can represent different semantics under the context of different ontologies, so relationships on mapping cannot be solely recognized by applying linguistic information. Discovering and utilizing structural information in ontology is also very important. In this paper, we propose a structure-based similarity spreading method for ontology matching which consists of three steps. We first select centroid concepts from both ontologies using similarities between entities based on their linguistic information. Second, we partition each ontology based on the set of centroid concepts recognized in it using clustering method. Third, we utilize a similarity spreading method to update the similarities between entities from two ontologies and apply a greedy matching method to establish the final mapping results. The experimental results demonstrate that our approach is very effective and can obtain much better results comparing to other similarity based and similarity flooding based algorithms.
机译:迄今为止的大多数常用本体映射方法是基于本体中暗示的语言信息。然而,不同的本体中的相同概念可以在不同本体的背景下代表不同的语义,因此通过应用语言信息不能仅识别映射上的关系。在本体中发现和利用结构信息也非常重要。在本文中,我们提出了一种基于结构的相似性扩展方法,用于本体匹配,其包括三个步骤。我们首先使用基于语言信息的实体之间的相似性选择来自两个本体的质心概念。其次,我们使用聚类方法根据其识别的集中概念组分区每个本体。第三,我们利用相似性扩展方法来更新来自两个本体的实体之间的相似性,并应用贪婪的匹配方法来建立最终映射结果。实验结果表明,我们的方法非常有效,并且可以获得与基于其他相似性和相似性泛滥的算法相比的更好的结果。

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