北京师范大学学报（自然科学版）2016，Vol.52Issue(4)：420-424,5.DOI:10.16360/j.cnki.jbnuns.2016.04.003
并行化的Apriori算法在海量医疗文档数据挖掘中的应用及优化∗
Optimization and application of Apriori algorithm based on MapReduce in medical big data
摘要
Abstract
To solve the problem that values hidden in big medical data cannot be properly mined,an MSPM system based on NoSQL and MapReduce is proposed.By key-value storage,complex and heterogeneous data are summed up in a unified and convenient format of transaction for Apriori.With MapReduce,complete global scanning and interest set counting solved the problem of low speed,high overhead and poor effectiveness of Apriori algorithm in its application to medical data mining.关键词
医疗文档大数据/非关系型数据库/MapReduce数据挖掘/Apriori/算法优化Key words
medical big data/NoSQL/MapReduce/data mining/Apriori/optimization分类
信息技术与安全科学引用本文复制引用
李伟,刘光明,孟祥飞,张真发..并行化的Apriori算法在海量医疗文档数据挖掘中的应用及优化∗[J].北京师范大学学报（自然科学版）,2016,52(4):420-424,5.基金项目
国家发改委高技术服务业基金资助项目(2014648) （2014648）
