Mining Frequent Itemset Using a New Approach Based on Sorting

Mining frequent itemset is an important concept in Data Mining. Association rules are used for analysing costumer behavior and the relationship among the data items. Generally the Association rules are used in market basket analysis to identify the costumer purchasing behavior. Apriori algorithm and Fp-Tree algorithms is most important algorithm for mining frequent itemsets. This paper presents a new and efficient algorithm for mining frequent itemsets, which is based on sorting technique. This algorithm reduces the full scan of the whole database for finding the frequent itemset.