摘要
为进一步提高频繁项集挖掘算法的可扩展性,对频繁项集的搜索空间以及FP-tree的操作方法进行了研究。在此基础上提出了基于frequent-pattern链表的高效频繁项集挖掘算法FPL-Growth。FPL-Growth运用递增构建候选项集策略和Apriori性质来缩小搜索空间,运用交叉计数方法快速获取频繁项集的支持数。最后的实验证明了该算法的有效性。
To further improve the scalability of the algorithm for frequent item-set mining,studies on the frequent item-set search space and the FP-tree operation method were made.On this basis,an efficient algorithm for frequent itemset mining based on the fre- quent-pattern list is presented,which employs the strategy of incremental construction of the candidate itemset and Apriori property to reduce the searching space,and gets support-count of the frequent itemset by intersecting tid-list. Lastly the algorithm is realized on experiment and is proved to be efficient.
出处
《微计算机信息》
2012年第10期491-493,共3页
Control & Automation
