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A Framework for Visualizing Association Mining Results

  • Gürdal Ertek
  • Ayhan Demiriz
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4263)

Abstract

Association mining is one of the most used data mining techniques due to interpretable and actionable results. In this study we propose a framework to visualize the association mining results, specifically frequent itemsets and association rules, as graphs. We demonstrate the applicability and usefulness of our approach through a Market Basket Analysis (MBA) case study where we visually explore the data mining results for a supermarket data set. In this case study we derive several interesting insights regarding the relationships among the items and suggest how they can be used as basis for decision making in retailing.

Keywords

Association Rule Frequent Itemsets Support Level Information Visualization Apriori Algorithm 
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 2006

Authors and Affiliations

  • Gürdal Ertek
    • 1
  • Ayhan Demiriz
    • 2
  1. 1.Faculty of Engineering and Natural SciencesSabanci UniversityIstanbulTurkey
  2. 2.Department of Industrial EngineeringSakarya UniversitySakaryaTurkey

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