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摘要
Whether for the Big Data or for the Internet of things, the heterogeneity of knowledge has always been an unavoidable problem. Ontologies have been acknowledged to be the core methodology for the heterogeneity of knowledge, and ontology matching is an important method to solve the heterogeneity of ontologies. This paper describes a novel ontology matching method to optimize the matching result. First, the method puts forward a novel ontology matching weight calculation method and a mathematical model to optimize the similarity integration. And then this method establishes an improved heuristic population evolution algorithm (shuffled frog leaping algorithm) to implement the optimization model. Finally, Ontology Alignment Evaluation Initiative (OAEI) test sets are used to evaluate the proposed method, and the feasibility and effectiveness of this method are proved by comparing with other matching systems in OAEI competition.
- 出版日期2019-4
- 单位山东农业大学
