计算机应用研究2017，Vol.34Issue(10)：2897-2900,2932,5.DOI:10.3969/j.issn.1001-3695.2017.10.004
基于MapReduce的top-k高效用模式挖掘算法
Top-k high utility pattern mining algorithm based on MapReduce
摘要
Abstract
High utility pattern mining has been widely applied in the field of data mining.Some top-k high utility pattern mining algorithms based on tree-like and list-like structures were proposed.However,tree-like algorithms generated a large number of candidates,and comparing operation was costly during the process of utility pattern growth in list-like algorithms.In addition,the amount of information data increased exponentially in information society.Thus,it required memory usage and computational cost in mining process,especially the dataset size was huge.In order to address above issues,this paper proposed top-k high utility pattern mining algorithm based on MapReduce,called TKHUP_MaR.TKHUP_MaR needed to scan database twice and used three MapReduce phases to parallelize top-k high utility pattern mining.The experiment results show that TKHUP_MaR is effective in the process of mining top-k high utility patterns on parallel environment.关键词
数据挖掘/top-k/高效用模式/MapReduce/并行算法Key words
data mining/top-k/high utility pattern/MapReduce/parallel algorithm分类
信息技术与安全科学引用本文复制引用
吴倩,王林平,罗相洲,崔建群,王海..基于MapReduce的top-k高效用模式挖掘算法[J].计算机应用研究,2017,34(10):2897-2900,2932,5.基金项目
国家自然科学基金资助项目(61370108) （61370108）
