Finding the N largest itemsets

Li Shen, Hong Shen, Paul Pritchard, Rodney Topor

Research output: Contribution to conferencePaperpeer-review

12 Citations (Scopus)


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.

Original languageEnglish
Number of pages12
Publication statusPublished - 1998
Externally publishedYes
EventProceedings of the 1988 International Conference on Data Mining - Rio de Janeiro, Brazil
Duration: 2 Sept 19984 Sept 1998


ConferenceProceedings of the 1988 International Conference on Data Mining
CityRio de Janeiro, Brazil


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