IFAMR: An Efficent Frequent Itemset Mining Algorithm Based on MapReduce

Liu Xiang-jia; Cheng Liang-lun

doi:10.12052/gdutxb.150120

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IFAMR: An Efficent Frequent Itemset Mining Algorithm Based on MapReduce

更新时间：2026-05-27

- IFAMR: An Efficent Frequent Itemset Mining Algorithm Based on MapReduce
- Vol. 34, Issue 2, Pages: 86-91(2017)
- 作者机构：
- 作者简介：
- 基金信息：
- DOI：10.12052/gdutxb.150120
  CLC： TP311
- Online First：09 March 2017，
  
  Published：2017
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刘祥佳, 程良伦. IFAMR:一种基于MapReduce的高效频繁项挖掘算法[J]. 广东工业大学学报, 2017, 34(2): 86-91.

Liu Xiang-jia, Cheng Liang-lun. IFAMR: An Efficent Frequent Itemset Mining Algorithm Based on MapReduce[J]. 2017, 34(2): 86-91.
刘祥佳, 程良伦. IFAMR:一种基于MapReduce的高效频繁项挖掘算法[J]. 广东工业大学学报, 2017, 34(2): 86-91. DOI： 10.12052/gdutxb.150120.

Liu Xiang-jia, Cheng Liang-lun. IFAMR: An Efficent Frequent Itemset Mining Algorithm Based on MapReduce[J]. 2017, 34(2): 86-91. DOI： 10.12052/gdutxb.150120.

摘要

针对单机无法高效地利用现有的并行计算框架来加快对海量数据进行频繁项挖掘的问题，根据Apriori算法基本原理，结合MapReduce并行计算模型的优势，在FAMR算法的基础上提出了一种改进的高效频繁项挖掘算法IFAMR.该算法首先采用AprioriTID算法来对原始数据进行预处理，删除所有的低频1-项集，然后计算出每次处理集（

）和最小支持度（

）的长度来确定Map操作结束后的最大合并候选集合.IFAMR算法减少了Map函数中的低频项集的生成，通过与已有的算法进行实验对比表明，该算法有效地减少了内存占用，提高了算法的挖掘效率.

Abstract

Considering that single host in the existing parallel computing framework is not efficient in accelerating massive data mining frequent item

an improved efficient algorithm for mining frequent item IFAMR is proposed

combining the advantages of the MapReduce parallel computing model according to the basic principle of Apriori algorithm and based on the algorithm FAMR. This algorithm first uses AprioriTID algorithm to preprocess the raw data

deleting all the low-frequency 1-itemsets

and then calculate the length of each transaction set (

) and minimum support (

) to determine the maximum merger candidate Map sets of operations. IFAMR algorithm reduces the Map function to generate a low-frequency item set

and the algorit

hms are proved by experimental comparison to have greatly reduced memory footprint and effectively improved the efficiency of the mining process.

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references

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