Research of multiple minimum supports frequent itemsets mining
多重最小支持度频繁项集挖掘算法研究

Mining frequent itemsets algorithm based on multiple minimum supports was studied in this paper, because sometimes setting different minimum supports to mine frequent itemsets is necessary. A new Minimum Support tree (MS-tree) algorithm and a MS-growth algorithm to mine all frequent itemsets based on Frequent Pattern growth (FP-growth) were proposed. It solves the problem of MSapriori algorithm that it cannot generate association rules without scanning the database again. The experimental results show that the proposed algorithm is comparable to FP-growth algorithm, but the former can solve the problem of multiple minimum supports.