文献类型：期刊文献

中文题名：一种高效并行关联规则挖掘新算法

英文题名：A Fast and Parallel Algorithm for Mining Association Rules Based on PC Cluster

作者：杨欣斌[1];孙京诰[1];陈霁威[1];黄道[1]

机构：[1]华东理工大学信息科学与工程学院,上海200237

年份：2003

卷号：29

期号：3

起止页码：295

中文期刊名：华东理工大学学报（自然科学版）

外文期刊名：Journal of East China University of Science and Technology

收录：CSTPCD;;Scopus;北大核心:【北大核心2000】；CSCD:【CSCD2011_2012】；

语种：中文

中文关键词：数据挖掘;关联规则;微机集群;并行挖掘;可扩性

外文关键词：data mining; association rules; PC cluster; parallel data mining; scalability

摘要：提出了一种在微机集群上实现的高效并行算法。该算法利用矩阵理论中上三角矩阵的良好性质 ,通过数据库约简、投影等操作 ,在微机集群的各节点上开展并行挖掘 ,从而提高挖掘算法的效率和可扩性。在微机集群上的实验证明 ,该算法能大大提高关联规则的挖掘效率 ,并具有良好的可扩性。
Mining association rules is an important issue in data mining community. Fruitful achievements have been made in this field during the past years. Many algorithms were proposed on the subject. However, effectiveness, scalability of the algorithms and attribute's contribution are still bottle necks to mining association rules. A fast and parallel algorithm for mining association rules based on PC cluster was presented in this paper. The algorithm works on the knots of the PC cluster after reducing and projecting operation according to the excellent properties of the upper triangle matrix. An experiment on the PC cluster testifies that the algorithm has the advantage of improving the effectiveness and scalability of mining association rules.