A fast algorithm for mining high utility itemsets

Abstract

Frequent itemset mining generates frequently purchased itemsets, which only considers the presence of an item in a transaction database. However, a frequent itemset may not be the itemset with high value. High utility itemset mining considers both of the profits and purchased quantities for the items, which is to find the itemsets with high utility for the business. The previous approaches for mining high utility itemsets first apply frequent itemset mining algorithm to find candidate high utility itemsets, and then scan the whole database to compute the utilities of these candidates. However, these approaches need to take a lot of time to generate all the candidate high utility itemsets, scan the whole database and search from a large number of candidate high utility itemsets to compute the utilities of these candidates. Therefore, the previous approaches are very inefficient. In this paper, we present an efficient algorithm for mining high utility itemsets. Our algorithm is based on a tree structure in which a part of utilities for the items are recorded. A mechanism is proposed to reduce the mining space and make our algorithm can directly generate high utility itemsets from the tree structure without candidate generation. The experimental results also show that our algorithm signif-icantly outperforms the previous approaches.