基于集合和位运算的频繁集挖掘优化算法  

An Optimized Algorithm for Mining Frequent Itemsets Based on Set and Bit Operation

作　　者：杨妮妮[1] 

机构地区：[1]辽宁石油化工大学,抚顺113001

出　　处：《科学技术与工程》2009年第23期7173-7175,7179,共4页Science Technology and Engineering

摘　　要：产生频繁项目集是关联规则挖掘中的一个关键步骤。在对Apriori算法分析的基础上,提出了一种基于集合和位运算的频繁项目集挖掘算法。该算法用位视图表示使用了每个项目的事务,通过对位视图进行位运算来计算每个项目集的支持数,避免了Apriori算法中多次扫描数据库的问题。Generating frequent itemsets is a critical step in association rule mining. Through the analysis of Apriori algorithm, a new algorithm for mining frequent itemsets based on set and bit operation is proposed. In this algorithm, digital view is used to express the transaction who used each item, and bit operating is used in digital view to calculate the number of support of each itemset. The problem of repeatedly scanning the database in Apriori algorithm is solved and operating efficiency is improved in the new algorithm.

关 键 词：数据挖掘 关联规则 频繁集 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]