Enhancing Association Rule Mining with a Profit Based Approach

  • Li Ming-Lai (Intelligent E-commerce Systems Laboratory, School of Computer Engineering, Inha University) ;
  • Kim Heung-Num (Intelligent E-commerce Systems Laboratory, School of Computer Engineering, Inha University) ;
  • Jung Jason J. (Intelligent E-commerce Systems Laboratory, School of Computer Engineering, Inha University) ;
  • Jo Geun-Sik (School of Computer Engineering, Inha University)
  • 발행 : 2005.11.01

초록

With the continuous growth of e-commerce there is a huge amount of products information available online. Shop managers expect to apply information techniques to increase profit and perfect service. Hence many e-commerce systems use association rule mining to further refine their management. However previous association rule algorithms have two limitations. Firstly, they only use the number to weight item's essentiality and ignore essentiality of item profit. Secondly, they did not consider the relationship between number and profit of item when they do mining. We address a novel algorithm, profit-based association rule algorithm that uses profit-based technique to generate 1-itemsets and the multiple minimum supports mining technique to generate N-items large itemsets.

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