(合肥工业大学 计算机与信息学院, 合肥 230009)
关键词：数据挖掘; 并行算法; 频繁项集
Effective parallel algorithm for mining frequent itemsets
WANG Dan-yang, TIAN Wei-dong, HU Xue-gang
(School of Computer & Information, Hefei University of Technology, Hefei 230009, China)
Abstract:There were problems in traditional parallel algorithms for mining frequent itemsets, such as load imbalance, frequent synchronization, large scale communication and so on. Aiming at solving these problems, this paper proposed a parallel algorithm with multi-transmitting redistributed data (MRPD). In MRPD, data was redistributed into some groups at step l, and all the groups were multi-transmitted according to the request of computer nodes. Each node would compute frequent itemsets asynchronously after having received one full group. Finally, resulted the integrated frequent itemsets. Theoretical analysis and experimental results suggest that MRPD is effective.......