An algorithm of association rules mining based on digit sequence

In order to avoid redundant calculation and reduce the time of scanning database, this paper proposes an algorithm of association rules mining based on digit sequence (DS). The algorithm firstly turns all transactions into digital transactions by binary, and then computing digit sequence of every attribute item. Finally, the algorithm uses forming digital pure subset of digital transaction to generate candidate frequent itemsets by ascending the value of digital pure subset, and uses computing dimension of digit sequence of attribute items to compute support of candidate frequent itemsets, this method is used to reduce the time of scanning transactions database. The algorithm only scans once database when mining all these association rules, which is different from presented algorithms of association rules mining. The experiment indicates that the efficiency of the algorithm is faster and more efficient than presented algorithms of association rules mining because the algorithm used two key techniques including generating digit sequence and digital pure subset.