Frequent Itemsets Discovery Algorithm and Its Application Based on Frequent Matrix

There are varieties of linkages among the properties of the data in a large database, These linkages are hidden in the data of the database, the purpose of association mining is to identify these hidden association rules. The discovery of association rules is based on frequent itemsets, so how could we make frequent itemsets fast and accurate is the main research of association data mining. In this paper, a matrix-based frequent discovery algorithm is raised according to the problems in the existing algorithms in finding frequent itemsets, and it has a practical application in the automobile fault parts association analysis system of automotive industry chain business intelligence platform..