An algorithm for mining frequent closed itemsets

The problem of mining frequent itemsets plays an essential role in mining association rules, but it is not necessary to mine all frequent itemsets, instead it is sufficient to mine the set of frequent closed itemsets, which is much smaller than the set of all frequent itemsets. In this paper, we present an efficient algorithm, FCI-Miner, for mining all frequent closed itemsets. It based on the improved FP-tree (frequent pattern tree), and used depth-first search strategy without generating conditional FP-trees and candidate itemsets. The experimental evaluation on a number of real and synthetic databases shows that our algorithm outperforms previous method in most cases.