Discovering of association rules in huge database

In this paper the problem of discovering association rules among items in extremely large databases has been considered. A novel mining algorithm has been proposed which can explore efficiently the large itemsets. one of the most popular algorithms is apriori . based on this algorithm this paper indicates the limitation of the original apriori algorithm of wasting time for scanning the whole database searching on the frequent itemsets , and presents an improvement on apriori by reducing that waste time depending on scanning only some transaction (by clustering the database and using new structures named subvector for each cluster).Performance and efficiency of proposed method has been compared with Apriori algorithms. Experimentsillustrate that proposed method will do better than apriori algorithm.

Keywords:

data mining , cluster table , association rules