Efficient Techniques for Mining High Utility Itemsets from Transactional Databases: A Survey

A Mining process has always remained as indivisible part in process of knowledge discovery. Especially when size of transactional datasets is large. Here we address this issue of mining high utility itemsets from large transactional databases and study different algorithms for discovering itemsets which has greater utility. Utility can be in form of profit earned or importance of item in set of transaction. Many algorithms are proposed for mining high item utility item sets, many of which degrades mining performance by producing large number of candidate itemsets. In this paper we mainly focuses on UP-Growth and UP-Growth plus algorithms. These algorithms outperforms other algorithms in terms of time and space requirement.