Maximal frequent itemset generation using segmentation approach

Abstract

Finding frequent itemsets in a data source is a fundamental operation behind Association Rule Mining. Generally, many algorithms use either the bottom-up or top-down approaches for finding these frequent itemsets. When the length of frequent itemsets to be found is large, the traditional algorithms find all the frequent itemsets from 1-length to n-length… (More)
DOI: 10.5121/ijdms.2011.3302

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