An N-list-based algorithm for mining frequent closed patterns

Two theorems for fast determining closed patterns based on N-list structure are presented.An N-list-based algorithm for mining closed patterns is then proposed.The proposed algorithm outperforms a number of classical algorithms in terms of runtime and memory usage in most cases. Frequent closed patterns (FCPs), a condensed representation of frequent patterns, have been proposed for the mining of (minimal) non-redundant association rules to improve performance in terms of memory usage and mining time. Recently, the N-list structure has been proven to be very efficient for mining frequent patterns. This study proposes an N-list-based algorithm for mining FCPs called NAFCP. Two theorems for fast determining FCPs based on the N-list structure are proposed. The N-list structure provides a much more compact representation compared to previously proposed vertical structures, reducing the memory usage and mining time required for mining FCPs. The experimental results show that NAFCP outperforms previous algorithms in terms of runtime and memory usage in most cases.

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