文献类型：期刊文献

英文题名：A new data mining algorithm based on MapReduce and hadoop

作者：Yang, Xianfeng[1]; Lian, Liming[2]

第一作者：Yang, Xianfeng

机构：[1] School of Information Engineering, Henan Institute of Science and Technology, Xinxiang, Henan, China; [2] Department of Mechanical and Electrical Engineering, Xinxiang University, Xinxiang Henan, China

第一机构：School of Information Engineering, Henan Institute of Science and Technology, Xinxiang, Henan, China

年份：2014

卷号：7

期号：2

起止页码：131-142

外文期刊名：International Journal of Signal Processing, Image Processing and Pattern Recognition

收录：EI(收录号：20142017714579)

语种：英文

外文关键词：Algorithms - Database systems - Parallel algorithms

摘要：The goal of data mining is to discover hidden useful information in large databases. Mining frequent patterns from transaction databases is an important problem in data mining. As the database size increases, the computation time and required memory also increase. Base on this, we use the MapReduce programming mode which has parallel processing ability to analysis the large-scale network. All the experiments were taken under hadoop, deployed on a cluster which consists of commodity servers. Through empirical evaluations in various simulation conditions, the proposed algorithms are shown to deliver excellent performance with respect to scalability and execution time. ? 2014 SERSC.