Open AccessNovel approach for semantic similarity cross ontology
Author(s) -
Leila Benaissa Kaddar,
Farah Ben-Naoum
Publication year - 2022
Publication title -
indonesian journal of electrical engineering and computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.241
H-Index - 17
eISSN - 2502-4760
pISSN - 2502-4752
DOI - 10.11591/ijeecs.v26.i1.pp493-504
Subject(s) - semantic similarity , computer science , wordnet , information retrieval , ontology , semantic integration , benchmark (surveying) , ontology alignment , similarity (geometry) , semantic web , cohesion (chemistry) , semantic computing , natural language processing , ontology based data integration , artificial intelligence , philosophy , chemistry , geodesy , epistemology , organic chemistry , image (mathematics) , geography
Measuring semantic similarity between terms is a crucial step in information retrieval and integration since it necessitates semantic content matching. Even though several models have been proposed to measure semantic similarity, these models are not able to effectively quantify the weight of relevant items that affect the semantic similarity judgment process. In this study, we present a new method for measuring semantic similarity between cross-ontologies, that consists of hybridizing node-based approaches such as WuP and Reda with the weight of similarity computed using WordNet. The proposed approach has been experimented to show its efficiency with two ontologies, configuration management tool (CMT) and ConfOf, from the conference domaine in the web ontology language (OWL) ontologies benchmark OAEI 2015 and evaluated using two metrics: density and cohesion.