Introducing a new calculation of weighted support and confidence

this paper proposes a weighted association rule mining algorithm based on matrix

which can improve the weighted frequent itemsets mining methods.Based on Apriori algorithm

it used matrixs storage structure

which scans the database only once and can quickly calculate the supporting degree of itemsets.Therefore

this algorithm greatly reduces the I / O

and can improve the weighted frequent itemsets generation effectively.By being used in the binding sales of supermarkets

shows that the algorithm can extract the relationship between product information and help the sales of goods effectively.