Evaluating market basket data with formal concept analysis

Alp Üstündağ, Mert Bal*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

1 Citation (Scopus)

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.

Original languageEnglish
Title of host publicationSpringer Proceedings in Complexity
PublisherSpringer
Pages113-118
Number of pages6
DOIs
Publication statusPublished - 2014

Publication series

NameSpringer Proceedings in Complexity
ISSN (Print)2213-8684
ISSN (Electronic)2213-8692

Bibliographical note

Publisher Copyright:
© Springer Science+Business Media Dordrecht 2014.

Keywords

  • Association rule
  • Association rule mining
  • Concept lattice
  • Formal concept analysis
  • Formal context

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