Algorithm of Mining Frequent Itemsets Based on Binary Representation

Discovery of frequent itemsets is the most fundamental and important problem in mining association rules. Proposes an algorithm based on binary representation makes use of the function of binary system, the algorithm can generate candidate itemsets and count their supports efficiently. Compared with the current algorithms, the function of this algorithm can be improved in some degree.