Enhancing Ontology Matching: Lexically and Syntactically Standardizing Ontologies Through Customized Lexical Analyzers
Ontology matching approaches 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 approaches 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 process that standardizes entity names both lexically and syntactically through a customized lexical analyzer tailored to the ontologies participating in the process. We evaluate this process efficacy using Alin and AML , ontology matching systems, along with the Anatomy and Conference tracks of OAEI, demonstrating an improvement in matching results.
Authors
- Jomar da Silva (ORCID: https://orcid.org/0000-0002-8228-0995)
- Fernanda Baião (ORCID: https://orcid.org/0000-0001-7932-7134)
- Kate Revoredo (ORCID: https://orcid.org/0000-0001-8914-9132)
- Cabral Lima (ORCID: https://orcid.org/0000-0003-1754-1666)
Institutions
- Universidade Federal do Rio de Janeiro (BR)
- Pontifícia Universidade Católica do Rio de Janeiro (BR)
- Humboldt-Universität zu Berlin (DE)
Publication Details
- Journal
- Semantic Web
- Published
- 2025-05-01
- DOI
- https://doi.org/10.1177/22104968251344447
- Primary Topic
- Semantic Web and Ontologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00