计算机工程与应用2012，Vol.48Issue(30)：147-150,4.DOI:10.3778/j.issn.1002-8331.2012.30.031
基于有序FP-tree的最大长度频繁项集挖掘算法
Algorithm for mining maximal length frequent itemsets based on order FP-tree
摘要
Abstract
The mining of frequent itemsets has been limited by the large number of resulting itemsets as well as the high computational cost. In many application domains, however, it is often sufficient to mine maximum length frequent itemsets. An order FP-tree-based algorithm is proposed for the mining problem. A field max-level is added in head-table to record the greatest height of item. In the mining process, only the item which max-level value is equal or greater than the length of existing maximum length frequent itemsets is traversed. Neither producing conditional pattern base nor constructing conditional frequent pattern tree recursively is needed, and the support of maximum length frequent itemsets is calculated. The experimental results show that the algorithm accelerates the speed to traverse the tree and improves the mining efficiency.关键词
最大长度频繁项集/数据挖掘/频繁项集/有序频繁模式树(FP)-treeKey words
maximum length frequent itemsets/ data mining/ frequent itemsets/ order Frequent Pattern(FP)-tree分类
信息技术与安全科学引用本文复制引用
廖福蓉,王成良..基于有序FP-tree的最大长度频繁项集挖掘算法[J].计算机工程与应用,2012,48(30):147-150,4.基金项目
重庆市重大科技攻关资助项目(CSTC2009AB2221). （CSTC2009AB2221）
