Enhancing Ontology Matching: Lexically and Syntactically Standardizing Ontologies Through Customized Lexical Analyzers

Ontology matching systems commonly leverage similarity metrics to establish mappings between entities in the ontologies participating in the process. However, the lack of standardized entity names across these ontologies can cause such metrics to overlook correct mappings. Generally, existing methodologies that focus on standardizing entity names neglect the ongoing matching process, leading to inaccurate results, and fail to address the syntactic standardization of entity names. To address these issues, we introduce a novel approach that standardizes entity names both lexically and syntactically through a customized lexical analyzer tailored to the ontologies participating in the process. We evaluate this approach's efficacy using Alin and AML, ontology matching systems, along with the Anatomy and Conference tracks of OAEI, demonstrating an improvement in matching results.