Research for Parallel Apriori Algorithm based on MPI
In order to improve the efficiency of Apriori mining algorithm for the Ultra-large-scale data sets, based on the partition for the candidate itemsets, this paper presents a parallel algorithm for mining association rules which directly using MPI for passing message base on the master-slave structural model. Simulation analysis showed that the mining time of the algorithm which proposed in this paper has a higher degree of shortening compared with the algorithm of Apriori. There have good parallelism and scalability especially for large-scale database mining.
Parallel computing parallel association rules the candidate set segmentation MPI
Pan weihao Sun jinguang Sun jinguang
Liaoning Technical University Huludao China
国际会议
北京
英文
2391-2394
2009-08-08（万方平台首次上网日期，不代表论文的发表时间）