Efficient Algorithms of Mining Top-k Frequent Closed Itemsets

摘要：

Top-k frequent closed itemsets mining has been studied extensively in data mining community. But the I/O cost of database scanning is still a bottle-neck problem in data mining. TFP-growth is a powerful algorithm to mine Top-k frequent closed itemsets and it is non-candidate generation algorithm using a special structure FP-tree. Many algorithms proposed recently are based on FP-tree. However, creating FP-tree from database must scan database two times. In order to enhance the efficiency of TFP- growth algorithms, propose a novel algorithm called QFPC which can create FP-tree with one database scanning. With QFPC, we can mine top-k frequent closed itemsets Efficiently

关键词： Frequent Closed Itemsets data mining database FP-tree Frequent Itemsets

作者: Lan Yongjie Qiu Yong

作者单位: Shandong Institute of Business and Technology,YanTai 264005 China

会议类型: 国际会议

会议名称: 第八届国际电子测量与仪器学术会议(Proceedings of 2007 8th International Conference on Electronic Measurement & Instruments)

会议地点: 西安

会议语种:英文

在线出版日期: 2007-08-16（万方平台首次上网日期，不代表论文的发表时间）