FREQUENT ITEMSET MINING OVER STREAM DATA:OVERVIEW

摘要：

　　During the past decade,stream data mining has been attracting widespread attentions of the experts and the researchers all over the world and a large number of interesting research results have been achieved.Among them,frequent itemset mining is one of main research branches of stream data mining with a fundamental and significant position.In order to further advance and develop the research of frequent itemset mining,this paper summarizes its main challenges and corresponding algorithm features.Based on them,current related results are divided into two categories: data-based algorithms and task-based algorithms.According to its taxonomy,the related methods belonging to the different categories and sub-categories are comprehensively introduced for better understanding.Finally,a brief conclusion is given.

关键词： Stream data Stream data mining Frequent itemset mining

作者: Z.G.Qu X.X.Niu J.Deng C. McArdle X.J.Wang

作者单位: Jiangsu Engineering Center of Network Monitoring,Nanjing University of Information Science & Technol Key Laboratory of Network and Information Attack & Defence Technology of MOE,Beijing University of P School of Electronic Engineering,Dublin City University,Dublin,Ireland

会议类型: 国际会议

会议名称: 2013IET International Conference on Information and Communication Technologies(IETICT2013)2013IET信息与通信技术国际会议

会议地点: 北京

会议语种:英文

页码: 28-33

在线出版日期: 2013-04-27（万方平台首次上网日期，不代表论文的发表时间）