Toward the Multilingual Semantic Web: Multilingual Ontology Matching and Assessment

The amount of multilingual data on the Web proliferates; therefore, developing ontologies in various natural languages is attracting considerable attention. In order to achieve semantic interoperability for Web, cross-lingual ontology matching techniques are highly required. This paper proposes a Multilingual Ontology Matching (MoMatch) approach different languages. MoMatch uses machine translation and string similarity identify correspondences across ontologies. Furthermore, we propose Quality Assessment Suite Ontologies (QASO) that comprises 14 metrics, out which seven metrics used assess quality process evaluate ontology. We present an in-depth comparison get most effective measure(s) between terms. To illustrate applicability our how it can be domains, two use cases. has been implemented using Scala Apache Spark under open-source license. have compared results with from Alignment Evaluation Initiative (OAEI 2020). achieved significantly high precision, recall, F-measure five state-of-the-art approaches.