Abstract

Ontology matching is an integral part for establishing semantic interoperability. One of the main challenges within the ontology matching operation is semantic heterogeneity, i.e. modeling differences between the two ontologies that are to be integrated. The semantics within most ontologies or schemas are, however, typically incomplete because they are designed within a certain context which is not explicitly modeled. Therefore, external background knowledge plays a major role in the task of (semi-) automated ontology and schema matching.

In this survey, we introduce the reader to the general ontology matching problem. We review the background knowledge sources as well as the approaches applied to make use of external knowledge. Our survey covers all ontology matching systems that have been presented within the years 2004–2021 at a well-known ontology matching competition together with systematically selected publications in the research field. We present a classification system for external background knowledge, concept linking strategies, as well as for background knowledge exploitation approaches. We provide extensive examples and classify all ontology matching systems under review in a resource/strategy matrix obtained by coalescing the two classification systems. Lastly, we outline interesting and yet underexplored research directions of applying external knowledge within the ontology matching process.

中文翻译：

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本体匹配的背景知识：调查

摘要

本体匹配是建立语义互操作性的一个组成部分。本体匹配操作中的主要挑战之一是语义异质性，即对要集成的两个本体之间的差异进行建模。然而，大多数本体或模式中的语义通常是不完整的，因为它们是在没有明确建模的特定上下文中设计的。因此，外部背景知识在（半）自动化本体和模式匹配任务中起着重要作用。

在本次调查中，我们向读者介绍了一般的本体匹配问题。我们回顾了背景知识来源以及用于利用外部知识的方法。我们的调查涵盖了 2004 年至 2021 年间在著名的本体匹配竞赛中展示的所有本体匹配系统，以及研究领域中系统选择的出版物。我们提出了一个用于外部背景知识、概念链接策略以及背景知识利用方法的分类系统。我们提供了广泛的示例，并在通过合并两个分类系统获得的资源/策略矩阵中对所有正在审查的本体匹配系统进行分类。最后，