基于Apriori算法的公共卫生事件应急条例自动匹配方法

Automatic Matching Method of Public Health Emergency Regulations Based on Apriori Algorithm

为了提高公共卫生事件应急响应和条例适用管理能力,提出基于Apriori算法的公共卫生事件应急条例自动匹配方法,构建公共卫生事件应急条例管理的大数据挖掘模型。根据语义融合方法,进行公共卫生事件应急条例的应急调度和挖掘。构建公共卫生事件应急条例分布有向图模型,采用图模型分析方法进行公共卫生事件应急条例匹配过程中的本体结构映射。通过语义特征融合方法进行公共卫生事件应急条例自动匹配和特征提取,建立公共卫生事件应急条例的属性特征分类模型,根据属性分布进行公共卫生事件应急条例的分类调阅。根据对公共卫生事件应急条例调阅结果进行寻优控制,采用Apriori算法实现公共卫生事件应急条例自动匹配过程中的收敛性控制和寻优学习,提高公共卫生事件应急条例自动匹配精度。仿真结果表明,采用该方法进行公共卫生事件应急条例自动匹配的收敛性较好,匹配精度较高,提高了公共卫生事件应急条例的适用能力。

In order to improve the ability of public health emergency response and regulations application management,an automatic matching method of public health emergency regulations based on Apriori algorithm is proposed,and a big data matching model of public health emergency regulations management is constructed.According to semantic fusion method,emergency scheduling and mining of public health emergency regulations are carried out,and a directed graph model of public health emergency regulations distribution is constructed.In this paper,we use graph model analysis method to map ontology structure in the matching process of public health emergency regulations,use semantic feature fusion method to automatically match and extract features,establish attribute feature classification model of public health emergency regulations,classify and read public health emergency regulations according to attribute distribution,and carry out optimization control according to the reading results of public health emergency regulations.Apriori algorithm is used to realize convergence control and optimization learning in the automatic matching process of public health emergency regulations,and improve the automatic matching accuracy of public health emergency regulations.Simulation results show that this method has good convergence and high matching accuracy for automatic matching of emergency regulations of public health events,and improves the applicability of emergency regulations of public health events.