Title :
Research for parallel apriori algorithm based on MPI
Author :
Weihao, Pan ; Jinguang, Sun
Author_Institution :
Liaoning Tech. Univ., Huludao, China
Abstract :
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.
Keywords :
application program interfaces; data mining; message passing; parallel algorithms; set theory; MPI; association rule mining; candidate itemset; master-slave structural model; message passing; parallel Apriori mining algorithm; ultra-large-scale data set; Algorithm design and analysis; Analytical models; Association rules; Data mining; Itemsets; Large-scale systems; Master-slave; Parallel algorithms; Partitioning algorithms; Scalability; MPI; Parallel computing; parallel association rules; segmentation; the candidate set;
Conference_Titel :
Computer Science and Information Technology, 2009. ICCSIT 2009. 2nd IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-4519-6
Electronic_ISBN :
978-1-4244-4520-2
DOI :
10.1109/ICCSIT.2009.5234538
