计算机技术与发展2018，Vol.28Issue(5)：99-102,4.DOI:10.3969/j.issn.1673-629X.2018.05.023
一种基于预判筛选的频繁项集挖掘算法
A Frequent Item-set Mining Algorithm Based on Prejudgment and Screening
摘要
Abstract
Frequent item-set mining as a key step in mining association rules,its performance is of great significance to mining association rules.Aiming at the shortcomings of classical Apriori algorithm like low efficiency and frequent scanning database,we propose a frequent item-set mining algorithm based on prejudge and screening through analysis of the principle and efficiency of the Apriori algorithm.It ob-tains the support-set of frequent item-set for prejudgment and screening by random sampling of the original dataset,so as to make the second pruning of the candidate set from original dataset.The damping factor and the compensation factor are introduced to correct the er-ror caused by the pre-selection screening to ensure the misjudgment rate and the omission rate of the algorithm.The experiments show that the proposed algorithm has better time efficiency.关键词
关联规则/Apriori/数据挖掘/预判筛选/频繁项集Key words
association rules/Apriori/data mining/prejudging and screening/frequent item-set分类
信息技术与安全科学引用本文复制引用
李德辰,吕一帆,赵学健..一种基于预判筛选的频繁项集挖掘算法[J].计算机技术与发展,2018,28(5):99-102,4.基金项目
国家自然科学基金(61373135,61401225,61572262,61502246,61672299) （61373135,61401225,61572262,61502246,61672299）
中国博士后科学基金(2015M581844) （2015M581844）
江苏省基础研究计划(自然科学基金)(BK20140883,BK20140894,BK20150869) （自然科学基金）
江苏省博士后科研资助计划项目(1501125B) （1501125B）
南京邮电大学校级科研基金(NY214101,NY215147) （NY214101,NY215147）
