An Algorithm for Mining Association Rules Based on Sets Operation

The discovery of association rules is an important data-mining task for which many algorithms have been proposed. However, the efficiency of these algorithms needs to be improved to handle real-world large datasets. In this paper, we present an efficient algorithm which is based on sets operation and compares it with traditional algorithms. The improved algorithm only needs to scan the database once to reduce computation time. Experiment results indicate that the new algorithm has good efficiency.