Application of multidimensional association rule techniques in manufacturing resource planning system

Association rules mining is a popular and well researched method in data mining research field , its purpose is to mine interesting relations between attributes in transaction database. Classic Apriori algorithm is one of the most influential association rules in mining boolean frequent itemsets algorithms, However, it has some disadvantages such as inefficient in generating candidate itemsets and frequently scanning database, it is not suitable for mining multiple dimensional data model which rise in recent years. A “second cut” method is proposed, which is on the basis of the Apriori algorithm. The algorithm applies to multidimensional mining association rules, and to some extent improved the efficiency of the algorithm. Referring to the manufacturing resource planning system (MRP) features of the retail points, the article sets up the sales association analysis data model based on the above algorithm. It proves that it can increase the sales dramatically by applying this methodology to the real business environment.