A Weighted Frequent Itemsets Mining Algorithm Based on Perpendicular Data Format

摘要：

　　mining frequent itemsets from a large dense type database may generate a large number of frequent itemsets,and it may generate redundant information in some cases.To address these problems,a weighted frequent itemsets mining algorithm based on perpendicular data format is proposed in this paper.The algorithm uses constrains of support and weight together,and then by uses itemsets extension to mine weighted frequent itemsets which meet the support and weight constraints at the same time.In order to reduce the number of candidate itemsets,the algorithm used two methods,the first is pruned using property of weighted effectively extension,and the second is use hash table to store weighted non frequent binomial set.

关键词： weighted sequential patterns perpendicular data format weighted frequent itemsets

作者: Jun Dong Haitao Lu

作者单位: College of Information Science and Engineering Yanshan University Qinhuangdao, China

会议类型: 国际会议

会议名称: 2015 Fifth International Conference on Instrumentation and Measurement,Computer,Communication and Control (IMCCC2015)(第五届仪器测量、计算机通信与控制国际会议)

会议地点: 秦皇岛

会议语种:英文

页码: 1198-1201

在线出版日期: 2015-09-18（万方平台首次上网日期，不代表论文的发表时间）