摘要
针对海量临床数据蕴藏的巨大价值难以有效挖掘的难题,将分散、破碎、异构的数据分为文档数据、二进制小文件和二进制大文件三类,并提出了一种适于数据挖掘的存储方案,该方案基于非关系型数据库Mongo DB实现了三类数据的一体化存储、统一规则访问及多样性查询、关联检索等功能。针对大文件直接访问造成系统性能不佳的问题,设计了一个由大文件各类关键特征信息组成的特征库,通过特征库的应用减少了大文件的直接访问。
To solve the problem that the great value hidden in the massive clinic-data can't be mined,the data is divided into three categories and a storage solution is proposed in this paper.In this solution,based on Mongo DB,data is organized into a special mode which is suitable for data mining.Many critical issues,including the integrated storage,unified query and associated access,can be solved.Simulation results show that the solution is practical and it can meet the needs of mining.
出处
《工业控制计算机》
2016年第1期121-123,共3页
Industrial Control Computer