摘要
MLS模型作为一种逼近模型被广泛应用于数据光滑、数值分析和统计等诸多领域.文章将MLS模型用于最优本体函数的计算,将本体图中每个顶点映射成实数后,通过顶点对应实数间的差值来确定它们的相似度.将新本体算法应用于GO本体和物理教育本体,通过实验结果表明新算法对特定应用领域的相似度计算和建立本体映射是有效的.
Mowng least-square method ＇s an approximation method tor data smoothing, numerical analysis, stansucs ana many other fields. We apply MLS method to get the optimal ontology function, and then each vertex is mapped into a real number. The similarity be- tween two vertices is determined by virtue of the difference of their corresponding real numbers. The new ontology algorithm is applied to the Go and the physical education ontologies, and the experiment results show that the new algorithms with efficiency in specific applica- tions for similarity measure and ontology mapping building.
出处
《红河学院学报》
2015年第5期14-16,共3页
Journal of Honghe University
基金
国家自然科学青年基金资助项目(11401519)
教育部科学技术研究重点项目(210210)
