计算机应用研究2024，Vol.41Issue(11)：3323-3328,6.DOI:10.19734/j.issn.1001-3695.2024.03.0089
基干部分参考匹配集合的混合遗传算法解决本体匹配问题
Optimizing ontology matching through hybrid genetic algorithm based on partial reference alignment
摘要
Abstract
The problem of heterogeneity between different ontologies becomes an obstacle to more intelligent and efficient knowledge sharing and communication between various applications.Ontology matching is an effective way to solve the above problems.In order to obtain high quality matching results,this paper proposed a hybrid genetic algorithm(HGA)based on PR A.The method adopted a stratified selection approach to utilize the heterogeneity feature among ontologies to solve the issue of semantic loss in the traditional PRA construction process,and proposed a new fitness function to further fully utilize the po-tential information in the PRA to solve the semantic loss problem from another perspective.In addition,the algorithm com-bined both genetic algorithm and stochastic hill climbing algorithm in order to find the optimal ontology matching solution in both global and local scales.Experimental results show that the algorithm is effective in obtaining high-quality matching results in different ontology matching tasks,and it also performs well in comparison with other cutting-edge methods.关键词
本体匹配/部分参考匹配集合/异质性/混合遗传算法Key words
ontology matching/partial reference alignment/heterogeneity/hybrid genetic algorithm分类
信息技术与安全科学引用本文复制引用
乔钰博,吕青,许诏云..基干部分参考匹配集合的混合遗传算法解决本体匹配问题[J].计算机应用研究,2024,41(11):3323-3328,6.基金项目
山西省省筹资金资助回国留学人员科研项目(2023061) （2023061）
