Abstract | ||
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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. |
Year | DOI | Venue |
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2016 | 10.3233/IFS-151872 | JOURNAL OF INTELLIGENT & FUZZY SYSTEMS |
Keywords | DocType | Volume |
Ontology integration,mapping,genetic algorithm,evolutionary method | Journal | 30 |
Issue | ISSN | Citations |
3 | 1064-1246 | 0 |
PageRank | References | Authors |
0.34 | 19 | 2 |
Name | Order | Citations | PageRank |
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Lingyu Zhang | 1 | 0 | 0.34 |
Bairui Tao | 2 | 0 | 0.34 |