## Abstract

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 language | English |
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Pages | 211-222 |

Number of pages | 12 |

Publication status | Published - 1998 |

Externally published | Yes |

Event | Proceedings of the 1988 International Conference on Data Mining - Rio de Janeiro, Brazil Duration: 2 Sept 1998 → 4 Sept 1998 |

### Conference

Conference | Proceedings of the 1988 International Conference on Data Mining |
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City | Rio de Janeiro, Brazil |

Period | 2/09/98 → 4/09/98 |