Pushing Frequency Constraint to Utility Mining Model

Traditional association rules mining (ARM) only concerns the frequency of itemsets, which may not bring large amount of profit. Utility mining only focuses on itemsets with high utilities, but the number of rich-enough customers is limited. To overcome the weakness of the two models, we propose a novel model, called general utility mining, which takes both frequency and utility into consideration simultaneously. By adjusting the weight of the frequency factor or the utility factor, this model can meet the different preferences of different applications. It is flexible and practicable in a broad range of applications. We evaluate our proposed model on a real-world database. Experimental results demonstrate that the mining results are valuable in business decision making.