计算机技术与发展2017，Vol.27Issue(8)：57-60,65,5.DOI:10.3969/j.issn.1673-629X.2017.08.012
一种自底向上的最大频繁项集挖掘方法
A Bottom-up Method for Mining Maximum Frequent Itemsets
摘要
Abstract
Mining frequent itemsets is the most critical step in mining association rules.Maximum frequent itemsets is a common compressed representation of frequent itemsets.In mining maximum frequent itemsets,the top-down methods would produce lots of candidate itemsets when the dimensions of maximum frequent itemsets is smaller than the number of frequent itemsets.The existing bottom-up methods need either traversal in database many times or building FP-tree recursively,and the prediction pruning strategies have further room for improvement.The algorithm of discovering maximum frequent itemsets based on minimum non-frequent itemsets named BNFIA has been proposed,which uses storage structure based on FP-tree and digs out the minimum non-frequent itemsets through a bottom-up approach first,then prunes with the minimum non-frequent itemsets to narrow search space for acquiring the maximum frequent itemsets fast through boundary frequent itemsets.Experimental results show that the proposed algorithm has performed better than the algorithm with same type.关键词
最大频繁项集/关联规则挖掘/FP-tree/最小非频繁项集/边界频繁项集Key words
maximum frequent itemsets/association rules mining/FP-tree/minimum non-frequent itemsets/boundary frequent itemsets分类
信息技术与安全科学引用本文复制引用
赵阳,吴廖丹..一种自底向上的最大频繁项集挖掘方法[J].计算机技术与发展,2017,27(8):57-60,65,5.基金项目
国家科技重点专项"核高基"(2015ZX01040-201) （2015ZX01040-201）
