Finding the N largest itemsets

The largest itemset in a given collection of transactions D is the itemset that occurs most frequently in D. This paper studies the problem of finding the N largest itemsets, whose solution can be used to generate an appropriate number of interesting itemsets for mining association rules. We present an efficient algorithm for finding the N largest itemsets. The algorithm is implemented and compared with the naive solution using the Apriori approach. We present experimental results as well as theoretical analysis showing that our algorithm has a much better performance than the naive solution. We also analyze the cost of our algorithm and observe that it has a polynomial time complexity in most cases of practical applications.