Profit Mining: From Patterns to Actions

  • Ke Wang
  • Senqiang Zhou
  • Jiawei Han
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2287)


A major obstacle in data mining applications is the gap between the statistic-based pattern extraction and the value-based decision making. We present a profit mining approach to reduce this gap. In profit mining, we are given a set of past transactions and pre-selected target items, and we like to build a model for recommending target items and promotion strategies to new customers, with the goal of maximizing the net profit. We identify several issues in profit mining and propose solutions. We evaluate the effectiveness of this approach using data sets of a wide range of characteristics.


Association Rule Target Item Minimum Support Concept Hierarchy Basic Prediction Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Ke Wang
    • 1
  • Senqiang Zhou
    • 1
  • Jiawei Han
    • 2
  1. 1.Simon Fraser UniversityCanada
  2. 2.University of Illinois at Urbana-Champaign

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