Title :
A New Improvement on Apriori Algorithm
Author :
Ji, Lei ; Zhang, Baowen ; Li, Jianhua
Author_Institution :
Inf. Security Eng. Sch., Shanghai Jiaotong Univ.
Abstract :
Efficiency has been concerned for several years in the research of association rules mining. In this paper, based on the improvement on the classical Apriori algorithm, a high-dimension oriented Apriori algorithm is proposed. Unlike existed Apriori improvements, our algorithm adopts a new method to reduce the redundant generation of sub-itemsets during pruning the candidate itemsets, which can obtain higher efficiency of mining than that of the original algorithm when the dimension of data is high. Theoretical proof and analysis are given for the rationality of our algorithm. Experiments with datasets of KDD Cup 1999 validate our work
Keywords :
data mining; Apriori algorithm improvement; association rules mining; data mining; high-dimension oriented Apriori algorithm; Algorithm design and analysis; Association rules; Character generation; Costs; Data mining; Information security; Itemsets; Iterative algorithms; Partitioning algorithms; Transaction databases;
Conference_Titel :
Computational Intelligence and Security, 2006 International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
1-4244-0605-6
Electronic_ISBN :
1-4244-0605-6
DOI :
10.1109/ICCIAS.2006.294255
