Ontology Alignment Technique for Improving Semantic Integration
Mohammad Mustafa Taye, Nasser Alalwan
Abstract
Mohammad Mustafa Taye, Nasser Alalwan
Abstract
A new technique for ontology alignment has been built by integrating important features of matching to achieve high quality results when searching and exchanging information between ontologies. The system is semiautomatic and enables syntactical and semantic interoperability among ontologies. Moreover, it is a multistrategy algorithm which can deal with and solve more than one critical problem. Therefore, it is likely to be more conveniently applicable in different domains. Also, we improve a semantic matcher based on combining lexical matcher with several rules and facts. Moreover, our technique illustrates the solving of the key issues related to heterogeneous ontologies, which uses combination-matching strategies to execute the ontology-matching task. Therefore, it can be used to discover the matching between ontologies. The main aim of the work is to introduce a method for finding semantic correspondences among heterogeneous ontologies, with the intention of supporting interoperability over given domains. Our goal is to achieve the highest number of accurate matches. Keywords-Ontology; Semantic Interoperability; Heterogeneous; Ontology Alignment.
OpenAlex reports 3 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
A new technique for ontology alignment has been built by integrating important features of matching to achieve high quality results when searching and exchanging information between ontologies. The system is semiautomatic and enables syntactical and semantic interoperability among ontologies. Moreover, it is a multistrategy algorithm which can deal with and solve more than one critical problem. Therefore, it is likely to be more conveniently applicable in different domains. Also, we improve a semantic matcher based on combining lexical matcher with several rules and facts. Moreover, our technique illustrates the solving of the key issues related to heterogeneous ontologies, which uses combination-matching strategies to execute the ontology-matching task. Therefore, it can be used to discover the matching between ontologies. The main aim of the work is to introduce a method for finding semantic correspondences among heterogeneous ontologies, with the intention of supporting interoperability over given domains. Our goal is to achieve the highest number of accurate matches. Keywords-Ontology; Semantic Interoperability; Heterogeneous; Ontology Alignment.
Key concepts: Computer science, Ontology, Ontology alignment, Semantic heterogeneity, Interoperability, Semantic interoperability, Upper ontology, Semantic integration