Efficiently Finding High Utility-Frequent Itemsets Using Cutoff and Suffix Utility

摘要：

　　High utility itemset mining is an important model with many real-world applications.But the popular adoption and successful industrial application of this model has been hindered by the following two limitations:(i)computational expensiveness of the model and(ii)infrequent itemsets may be output as high utility itemsets.This paper makes an effort to address these two limitations.A generic high utility-frequent itemset model is introduced to find all itemsets in the data that satisfy user-specified minimum support and minimum utility constraints.Two new pruning measures,named cutoff utility and suffix utility,are introduced to reduce the computational cost of finding the desired itemsets.A single phase fast algorithm,called High Utility Frequent Itemset Miner(HU-FIMi),is introduced to discover the itemsets efficiently.Experimental results demonstrate that the proposed algorithm is efficient.

关键词： Data mining Itemset mining Utility itemset

作者: R.Uday Kiran T.Yashwanth Reddy Philippe Fournier-Viger Masashi Toyoda P.Krishna Reddy Masaru Kitsuregawa

作者单位: National Institute of Information and Communications Technology,Tokyo,Japan;The University of Tokyo, International Institute of Information Technology-Hyderabad,Hyderabad,India Harbin Institute of Technology(Shenzhen),Shenzhen,China The University of Tokyo,Tokyo,Japan The University of Tokyo,Tokyo,Japan;National Institute of Informatics,Tokyo,Japan

会议类型: 国际会议

会议名称: The 23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining (第23届亚太知识发现和数据挖掘国际会议(PAKDD2019)

会议地点: 澳门

会议语种:英文

页码: 191-203

在线出版日期: 2019-04-14（万方平台首次上网日期，不代表论文的发表时间）