A Modified Apriori Algorithm with Its Application in Instituting Cross-Selling Strategies of the Retail Industry

Retail industry accumulates a large number of retail sales data. Using Apriori algorithm we can find the association rules among commodities and institute cross-selling strategies so that we can improve the profits of retail industry. Based on the analysis of the efficiency of the typical Apriori algorithm we provide a modified method to improve the performance of the Apriori algorithm by reducing the scale of the candidate item set C_k and the spending of I/O. The paper also describes the application of the modified Apriori algorithm in search of the association rules of sales data of commodities by combining with the actual sales data, so that the feasibility of the algorithm is proved.