The average utility measure reveals a better utility effect of combining several items than the original utility measure. In this paper, we propose a two-phase average-utility mining algorithm that can incrementally maintain the high average-utility itemsets as a database grows. Based on the concept of the FUP algorithm, the proposed algorithm combines the previously mined information from the original database and the new mined results from the newly inserted transactions to speed up the mining process. Experimental results also show the effectiveness and efficiency of the proposed algorithm.
['Tzung-Pei Hong', 'Cho-Han Lee', 'Shyue-Liang Wang']
An Incremental Mining Algorithm for High Average-Utility Itemsets