Article ID Journal Published Year Pages File Type
10321827 Expert Systems with Applications 2015 26 Pages PDF
Abstract
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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Physical Sciences and Engineering Computer Science Artificial Intelligence
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