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Evaluating Market Basket Data with Formal Concept Analysis

  • Alp Üstündağ
  • Mert Bal
Conference paper
Part of the Springer Proceedings in Complexity book series (SPCOM)

Abstract

Knowledge discovery process from databases has gained importance recently. Finding and using the valuable and meaningful data which is hidden in large databases can have strategic importance for the organizations to gain competitive advantage. In this context, data mining methods are used to analyze customer purchasing data which is called “market basket analysis”. This analysis provides insight into the combination of products within a customer’s ‘basket’. In this study, a market basket analysis is conducted to identify a customer purchasing behaviour with Formal Concept Analysis (FCA). The FCA technique is one of the data mining methods using formal contexts and concept lattices. So, this method provides to create association rules based on lattices reflecting the relationships among the attributes in a database.

Keywords

Association Rule Association Rule Mining Concept Lattice Formal Context Formal Concept Analysis 
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 Science+Business Media Dordrecht 2014

Authors and Affiliations

  1. 1.Istanbul Technical UniversityIstanbulTurkey
  2. 2.Yildiz Technical UniversityIstanbulTurkey

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