Mining High Average-Utility Itemsets with an Indexed Projection Technique

An itemset in traditional utility mining only considers individual profits and quantities of items in transactions but not its itemset length. The average-utility measure, which is the total utility of an itemset divided by its number of items within it, was then proposed to reveal a better utility effect than the original utility one. However, their proposed approach was based on the principle of level-wise processing to find high average-utility itemsets from a database. In this paper, we thus propose an efficient average-utility mining approach which adopts a projection technique and an indexing mechanism to speed up the execution and reduce the memory requirement in the mining process. Finally, the experimental results on a real dataset show the superior performance of the proposed