微型电脑应用2018，Vol.34Issue(1)：28-31,40,5.
基于社会计算的大数据集关联规则的研究
Research on Association Rules for Large Data Sets Based on Social Computing
摘要
Abstract
The simplification of the association rules of data mining is a very important topic in the field of social computing,and the problem of the existing scheme of frequency is not valid for the relatively large data sets.A new method for mining WTabular algorithm is proposed.The algorithm assigns a weight for each rule,removes less important rules and combines with the Quine McCluskey algorithm of rules to simplify rules.Experiments show that compared with the traditional representation al gorithms,such as APRIORI algorithm and frequent pattern (FP) growth algorithm,this method can effectively improve the support degree,reliability,rule reduction rate and processing time.关键词
数据挖掘/简化关联规则/社会计算/奎因-麦克拉斯基算法Key words
Data mining/association rule simplification/social computing/Quine-Mccluskey algorithm分类
信息技术与安全科学引用本文复制引用
马宪敏..基于社会计算的大数据集关联规则的研究[J].微型电脑应用,2018,34(1):28-31,40,5.基金项目
全国高等院校计算机基础教育研究会独立学院及民办高校计算机基础教学研究与改革课题(AFCEC-2016-15) （AFCEC-2016-15）
