The Mining Algorithm of Frequent Itemsets based on Mapreduce and FP-tree

被引：0

作者：

He, Bo ^{[1
]}

Zhang, Hongyuan ^{[1
]}

Pei, Jianhui ^{[1
]}

机构：

[1] ChongQing Univ Technol, Sch Comp Sci & Engn, Chongqing 400054, Peoples R China

来源：

2017 INTERNATIONAL CONFERENCE ON COMPUTER NETWORK, ELECTRONIC AND AUTOMATION (ICCNEA) | 2017年

关键词：

FP-tree; Mapreduce; Frequent itemsets; Big data; Data mining;

D O I：

10.1109/ICCNEA.2017.59

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The date mining based on big data was a very important field. In order to improve the mining efficiency, the mining algorithm of frequent itemsets based on mapreduce and FP-tree was proposed, namely, MAFIM algorithm. Firstly, the data were distributed by mapreduce. Secondly, local frequent itemsets were computed by FP-tree. Thirdly, the mining results were combined by the center node. Finally, global frequent itemsets were got by mapreduce and the search strategy. Theoretical analysis and experimental results suggest that MAFIM algorithm is fast and effective.

引用

页码：108 / 111

页数：4

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