An Efficient Algorithm for Mining Erasable Itemsets

摘要：

Mining erasable itemsets first introduced in 2009 is one of new emerging data mining tasks. In this paper, we present a new data representation called PID_list, which keeps track of the id_nums (identification number) of products that include an itemset. Based on PIDJist, we propose a new algorithm called VME for mining erasable itemsets efficiently. The main advantage of VME algorithm is that the gain of an itemset can be computed efficiently via union operations on product id_nums. In addition, VME algorithm can also automatically prune irrelevant data. For evaluating VME algorithm, we have conducted experiments on six synthetic product databases. Our performance study shows that the VME algorithm is efficient and is on average over two orders of magnitude faster than the META algorithm, which is the first algorithm for dealing with the problem of erasable itemsets mining.

关键词： Data mining Erasable Itemsets Algorithm PID_list

作者: Zhihong Deng Xiaoran Xu

作者单位: Key Laboratory of Machine Perception (Ministry of Education),School of Electronics Engineering and C Key Laboratory of Machine Perception (Ministry of Education),School of Electronics Engineering and C

会议类型: 国际会议

会议名称: 6th International Conference on Advanced Data Mining and Applications(第六届先进数据挖掘及应用国际会议 ADMA 2010)

会议地点: 重庆

会议语种:英文

页码: 214-225

在线出版日期: 2010-11-19（万方平台首次上网日期，不代表论文的发表时间）