An Efficient Generation of Potential High Utility Itemsets from Transactional Databases

Abstract:- The importance of Utility Mining is to identify the itemsets with maximum utilities, by considering profit, quantity, cost or other user preferences. An Efficient discovery of high utility itemsets from transactional databases refers to finding the itemsets with high utility like profits. High utility itemsets mining extends frequent pattern mining and weighted frequent mining to discover itemsets in a transaction database with utility values above a given threshold. We proposed an efficient algorithm namely UP-Growth+ (Utility Pattern Growth+), which improves the mining performance in terms of time and space complexities. The information of high utility itemsets is maintained in tree-based data structure named as UP-Tree (Utility Pattern Tree).The performance of both UP-Growth and UP-Growth+ is compared with the state-of- the-art algorithms on different types of datasets. UP-Growth+ is not only reduces the number of candidates effectively but also better than other algorithms substantially in terms of execution time and space requirement, especially when the database contains lots of long transactions