Efficient Mining Algorithm For Reducing Number Of Itemsets Using Chud (International Journal of Engineering and Computer Science, 2017)
Data Mining plays an essential role for mining useful pattern hidden in large databases. Apriori algorithm  is used to find frequent itemsets in large databases. Apriori is a Bottom-up generation of Frequent item set combinations. Frequent itemset mining may discover the large amount of frequent but low revenue itemsets and lose the information on the valuable itemsets having low selling frequencies. High Utility Itemset mining identifies itemsets whose utility satisfies the given threshold. It allows the users to quantify the usefulness or preferences of items using different values. A High Utility Itemset which is not included in another itemset having the same support is called Closed High Utility Itemset. Mining High utility itemsets uses Apriori algorithm which takes the Input as Frequent Itemsets from the Transactional database, profit, and price and gives the High Utility Itemsets as the Output. To mine the Closed High Utility Itemsets the system addresses an efficient Depth-First search algorithm named CHUD.Keywords: Frequent item set, High Utility Itemset, Closed High Utility Itemset, CHUD.