ASSOCIATION-RULES-BASED DATA IMPUTATION WITH SPARK

被引：0
|
作者：
Qu, Zhaowei [1 ]
Yan, Jianru [1 ]
Yin, Sixing [1 ]
机构：
[1] Beijing Univ Posts & Telecommun, Beijing 100876, Peoples R China
来源：
PROCEEDINGS OF 2016 4TH IEEE INTERNATIONAL CONFERENCE ON CLOUD COMPUTING AND INTELLIGENCE SYSTEMS (IEEE CCIS 2016) | 2016年
关键词：
Association rules; Data preprocessing; Spark; Distributed algorithm;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Due to technical bottlenecks and errors caused by artificial operation, the problem of incomplete data always exists in big data research. Traditional data imputation algorithms incur high complexity and the accuracy cannot reach the desired level. At the same time, analysis and computation involved in mass data makes limitation of traditional algorithms and computing platform more noticeable. In this paper, we propose a data imputation method based on Apriori algorithm, and implement the corresponding algorithm on the distributed computing system built with Spark, The experimental results show that the proposed algorithm outperforms a traditional data imputation algorithm in terms of efficiency and accuracy.
引用
收藏
页码：145 / 149
页数：5
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