An Efficient Approach Using AIF Algorithm to Increase the Sales of Infrequent Items

Frequent itemset mining is one of the active research area in data mining. There exist a purpose to look after different data and its applications. At the same time, infrequent itemset mining plays an eminent role . Based on the minimum threshold the frequent items are generated using dFIN Algorithm. The infrequent items are extracted from the transaction dataset. The sales of infrequent items are promoted using AIF (Association of infrequent item with frequent itemset) Algorithm. The infrequent items are extracted based on the threshold. The infrequent item is mapped with the largest frequent item. The mapping is based on the least expiry date of infrequent item and the largest support count of frequent items. Through this way the sales of infrequent items gets increased.