Algorithms for Mining Frequent Itemsets Based on Upper Triangular Frequent Matrix

The traditional algorithms for mining association frequent patterns generate conditional sub tables,which costs much runtime and memory space.To solve these problems,a new algorithm FIA(Frequent Iternset Algorithm)is proposed. The FIA algorithm adopts a binary of symbols to compress the store data.The algorithm using logic of symbols to express data in a database,which only after one scan,and establish a binary vector and upper triangular frequent matrix, according to the both to produce a set of frequently.Thereby effectively narrowing the search space,speed up the processing speed.Through analysis showed that,FIA algorithm more effective than Apriori algorithm.