Large-Scale Ontology Alignment- An Extraction Based Method to Support Information System Interoperability

Mourad Zerhouni, S. Benslimane
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Abstract

Ontology alignment is an important way of establishing interoperability between Semantic Web applications that use different but related ontologies. Ontology alignment is the process of identifying semantically equivalent entities from multiple ontologies. This is not always obvious because technical constraints such as data volume and execution time are determining factors in the choice of an alignment algorithm. Nowadays, partitioning and modularization are two main strategies for breaking down large ontologies into blocks or ontology modules respectively to align ontologies. This article proposes ONTEM as an effective alignment method for large-scale ontology based on the ontology entities extraction. This article conducts a comprehensive evaluation using the datasets of the OAEI 2018 campaign. The obtained results are promising, and they revealed that ONTEM is one of the most effective systems.
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大规模本体对齐——一种支持信息系统互操作性的抽取方法
本体对齐是在使用不同但相关的本体的语义Web应用程序之间建立互操作性的重要方法。本体对齐是从多个本体中识别语义等效实体的过程。这并不总是很明显,因为数据量和执行时间等技术限制是选择对齐算法的决定因素。目前,划分和模块化是将大型本体分别分解为块或本体模块以实现本体对齐的两种主要策略。本文提出了一种基于本体实体抽取的大规模本体对齐方法——ONTEM。本文使用OAEI 2018活动的数据集进行了全面评估。所获得的结果是有希望的,他们揭示了ONTEM是最有效的系统之一。
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