A Graph-Based Ontology Matching Framework
Küçük Resim Yok
Tarih
2023
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Ontologies are domain-specific metadata that describe relationships between a specific field's properties, sample data of this field, and properties developed for many different purposes. Also, ontologies can be defined by other names within the same domain. Ontology matching algorithms eliminate definition differences and find similarities between existing ontologies. Ontology matching algorithms are used especially for information management, data integration, information extraction, etc. In this study, a graph-based framework is proposed to match large ontologies. This framework is aimed to divide the large ontologies into small pieces and then matches them using sub-graph mining algorithms. Karger algorithm and CP (clique percolation and nearest neighbor) algorithm are used to divide large ontologies. Both algorithms were applied to ontologies for the first time. In the next step, these obtained sub-parts are matched by using sub-graph mining algorithms. GraMi and gSpan algorithms were selected and were used for the first time in the field of ontology matching. We validated our framework using Anatomy and Conference data sets. Also, the proposed framework is compared with widely used in the literature AML and Falcon-AO matching algorithms. According to obtained the results, it is seen that GraMi is better than matching algorithms.
Açıklama
Anahtar Kelimeler
Ontology alignment, Ontology matching, Graph algorithms, Graph theory, Graph mining, Alignment
Kaynak
New Generation Computing
WoS Q Değeri
Q2
Scopus Q Değeri
Q3
