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The cleaning method of duplicate big data based on association rule mining algorithm

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成果类型:
期刊论文
作者:
Ming Wu
通讯作者:
Wu, M.
作者机构:
[Ming Wu] College of Information and Electronic Engineering, Hunan City University, Yiyang, Hunan, 413000, China
通讯机构:
[Wu, M.] C
College of Information and Electronic Engineering, Yiyang, China
语种:
英文
关键词:
association rule mining algorithm;cleaning;duplicate big data;frequent items;low cleaning efficiency;serious memory consumption
期刊:
International Journal of Autonomous and Adaptive Communications Systems
ISSN:
1754-8632
年:
2023
卷:
16
期:
2
页码:
220-231
机构署名:
本校为第一机构
院系归属:
信息与电子工程学院
摘要:
In order to overcome the problems of low cleaning efficiency and serious memory consumption in traditional large data cleaning methods, this paper proposes a new cleaning method of repeated big data based on association rule mining algorithm. This method uses association rule mining algorithm to obtain the frequent itemsets of repeated big data after repeated cycle calculation. At the same time, the output mode of the algorithm is optimised in parallel, and the Hadoop interface is modified to change the reading mode of MapReduce. The first freq...

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