基于进化算法的生物医学本体匹配技术  

Evolutionary algorithm based biomedical ontology matching technique

作　　者：王颖 薛醒思 卢家伟 黄艺坤 WANG Ying;XUE Xingsi;LU Jiawei;HUANG Yikun(School of Information Science and Engineering,Fujian University of Technology,Fuzhou 350118,P.R.China;Department of Information Technology,Concord University College Fujian Normal University,Fuzhou 350117,P.R.China)

机构地区：[1]福建工程学院信息科学与工程学院,福州350118 [2]福建师范大学协和学院信息技术系,福州350117

出　　处：《重庆大学学报》2023年第6期130-135,共6页Journal of Chongqing University

基　　金：国家自然科学基金资助项目(62172095);福建省自然科学基金资助项目(2020J01875);福建省本科高校教学改革研究项目(FBJG20190156)。

摘　　要：由于生物医学本体拥有规模庞大的概念和复杂概念间关系,已有本体匹配技术难以高效确定生物医学本体匹配结果。为解决这一问题,构建了生物医学本体匹配问题优化模型,提出基于进化算法的生物医学本体匹配技术来确定最优匹配结果。在求解生物医学本体匹配问题时,采用一种新的生物医学本体概念相似度度量来确保匹配结果质量,并通过基于推理的概念对剪枝技术缩小算法的搜索空间,提高算法效率。实验结果表明,基于进化算法的生物医学本体匹配技术能有效匹配生物医学本体。Since biomedical ontologies own large-scale concepts and complex relationships among them,the existing ontology matching techniques are not able to determine the biomedical alignment efficiently.To tackle this challenge,a mathematical optimal model for biomedical ontology matching problem is first constructed,and then an evolutionary algorithm(EA)based biomedical ontology matching technique is proposed to determine the optimal alignment.In particular,when solving the biomedical ontology matching problem,a novel biomedical concept similarity measure is utilized to ensure the quality of the alignment,and a reasoning-based concept pruning approach is used to reduce the algorithm's search space and improve its efficiency.The experimental results show that EA-based biomedical ontology matching technique is able to match the biomedical ontologies effectively and efficiently.

关 键 词：进化算法 生物医学本体匹配 概念对剪枝 

分 类 号：TP182[自动化与计算机技术—控制理论与控制工程]