基于高阶项目集的频繁项目集发现算法

摘要

为了提高关联规则数据挖掘的效率,在研究Apriori算法原理和相关文献的基础上,提出了一种基于高阶项目集的频繁项目集发现算法.本算法不同于逐层迭代的搜索方式,而是采用从求解所有的高阶频繁m-项目集人手的方式,来发现隐藏在事务数据库中的频繁项目集.本算法避免了大量的候选项目集的产生,并且对数据库仅需进行有限次数的扫描,从而体现了算法的高效性.%In order to improve the efficiency of mining association rules, and based on the research on the Apriori algorithm and many related documents, a frequent itemsets discovery algorithm based on the high-dimensional itemsets is presented. Defferent from the method of iterative searching layer by layer, in order to discovering the frequent itemsets in the transactions database, the algorithm starts with solving all the high-dimensional frequent mitemsets. The algorithm avoids generating a mass of candidate itemsets, and the database is scanned only several times. So the efficiency of algorithm is very high.