A Three-Scan Mining Algorithm for High On-Shelf Utility Itemsets

نویسندگان

  • Guo-Cheng Lan
  • Tzung-Pei Hong
  • Vincent S. Tseng
چکیده

In this paper, we introduce a new kind of patterns, named high on-shelf utility itemsets, which consider not only individual profit and quantity of each item in a transaction but also on-shelf periods in a database. We have thus proposed a 3-scan mining algorithm to efficiently discover the itemsets. The proposed approach adopts a new pruning strategy and an itemset-generation mechanism to prune redundant candidate itemsets early and to systematically check the itemsets from transactions. Experimental results also show its performance.

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تاریخ انتشار 2013