基于电子病历的频繁模式挖掘研究

提出了对电子病历挖掘频繁集的一种方法,该方法引入了一种称为模式仓库结构,它以简洁方式来存储所有相关信息且可直接导出FP-tree;给出了一种称为FP-aprgrowth算法,它综合了Apriori方法和FP-growth方法二者的优点,接着阐明了FP-tree映射到决策树的原理和方法。最后给出一个例子显示其处理过程及效率。

Research on Frequent Patterns Mining Based on Electronic Patient Record

This paper proposes a method for mining frequent patterns in Electronic Patient Record(EPR):We design a new structure called Pattern Repository(PR),Which stores all of the relevant information in a highly compact form and allows direct derivation of the FP-tree;we give a patterns mining algorithm named FP-aprgrowth that integrates Apriori candidate generation into FP-growth method,found frequent patterns quickly with a minimum of resources.It clarifies the theory and method of mapping FP-tree to decision tree.Finally,an example shows efficiency and process.