Email this article Empirical Evaluations On Real And Synthetic Datasets State Of The Art Utility Mining Algorithms
Abstract
We have considered the issue of best k high utility itemsets mining, where k is the coveted number of high utility itemsets to be mined. Two effective calculations TKU (mining Top-K Utility itemsets) and TKO (mining Top-K utility itemsets in One stage) are proposed for mining such itemsets without setting least utility limits. TKU is the initial two-stage calculation for mining top-k high utility itemsets, which joins five techniques PE, NU, MD, MC and SE to adequately raise the fringe least utility edges and further prune the hunt space. Then again, TKO is the first stage algorithm produced for top-k HUI mining, which incorporates the novel methodologies RUC, RUZ and EPB to extraordinarily enhance its execution. The proposed calculations have great versatility on extensive datasets and the execution of the proposed algorithms is near the ideal instance of the cutting edge two-stage and one-stage utility mining algorithms.
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