Optimization and Application in Medical Big Document-Data of Apriori Algorithm based on MapReduce

被引：0

作者：

Li Wei ^{[1
]}

Liu Guangming ^{[1
]}

Shao Yachao ^{[2
]}

Liu Junlong ^{[2
]}

Zuo You ^{[2
]}

机构：

[1] Natl Univ Def Technol, Changsha, Hunan, Peoples R China

[2] Natl Supercomp Ctr Tianjin, Tianjin, Peoples R China

来源：

2016 INTERNATIONAL CONFERENCE ON COMPUTER COMMUNICATION AND INFORMATICS (ICCCI) | 2016年

关键词：

component; Medical big data; NoSQL; MapReduce; Data Mining; Apriori; optimization;

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

For the challenges of redundancy, multi-dimension, complex and heterogeneous in medical documents, and to solve the problem that the value hidden in the huge amounts of medical document-data can't be mined, this paper proposed a system called MSPM based on NOSQL and MapReduce. Through storage of key-value pairs, complex and heterogeneous datas are summed up in a unified and convenient format of transaction for Apriori. Then Apriori is executed in parallel through MapReduce. At last, with the strategies of generating all the candidate sets non-recursively and constraint count for candidate sets of interest, it can solve the problem of low speed, high overhead and poor effectiveness for Apriori algorithm in the application of medical data. Testing results has shown the algorithm of optimization is available.

引用

页数：5

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