Abstract: 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 matrix's 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.