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Article type: Research Article
Authors: Zhang, Lingyu* | Tao, Bairui
Affiliations: Computing Centre, Qiqihar University, Heilongjiang Province, China
Correspondence: [*] Corresponding author. Lingyu Zhang is with the Computing Centre, Qiqihar University, Qiqihar 161006, Lecture, Doctor, China. Tel./Fax: +86 24 83681582; E-mail: [email protected].
Abstract: Ontology integration is an important work when integrating information from heterogeneous ontologies into an ontology. The existing methods about ontology integration cannot effectively make full use of non-1-1 mappings, which are very common in the real world. Furthermore, these methods only stated that the concept-pairs with mappings should be integrated, but not gave the specific operations for it. Therefore, these methods cannot describe a complete framework for ontology integration. To this end, this paper proposes a framework for Ontology Integration based on Genetic Algorithm, called OI-GA. During the process of integrating ontologies, OI-GA firstly creates mappings between them based on similarity measures. Next, OI-GA finds out all the non-1-1 mappings from mappings, and provides an evolutionary method to extract 1-1 mappings from them. Finally, all the concepts belonging to different ontologies are integrated into a new knowledge base called integrated ontology. Experimental results indicate that OI-GA performs encouragingly well in the optimization of mapping set as well as in the integration of ontologies from the real world.
Keywords: Ontology integration, mapping, genetic algorithm, evolutionary method
DOI: 10.3233/IFS-151872
Journal: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 3, pp. 1643-1656, 2016
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