An Efficient Technique for mining Association rules using Enhanced Apriori Algorithm

Abstract

There are Various mining algorithms of association rules. One of the most popular algorithm is Apriori that extracts frequent itemset from large database and getting the association rule for discovering the knowledge. this paper pitfalls the limitation of the original Apriori algorithm for wasting time for scanning the whole database searching on to the frequent itemsets, and presents an technique on Apriori by reducing that wasted time depending on scanning only some transactions whose support value is bigger than 25% of minimum Support is taken as frequent item set and is added to the frequent item sets and then rules are formed. An enhanced Apriori algorithm may find the tendency of a customer on the basis of frequently purchased item-sets The proposed algorithm is useful as a frequent item sets predictor with lower number of scans.
DOI: 10.17762/ijritcc2321-8169.150638