Re-mining item associations: Methodology and a case study in apparel retailing

Ayhan Demiriz, Gürdal Ertek, Tankut Atan, Ufuk Kula

Research output: Contribution to journalArticlepeer-review

16 Citations (Scopus)


Association mining is the conventional data mining technique for analyzing market basket data and it reveals the positive and negative associations between items. While being an integral part of transaction data, pricing and time information have not been integrated into market basket analysis in earlier studies. This paper proposes a new approach to mine price, time and domain related attributes through re-mining of association mining results. The underlying factors behind positive and negative relationships can be characterized and described through this second data mining stage. The applicability of the methodology is demonstrated through the analysis of data coming from a large apparel retail chain, and its algorithmic complexity is analyzed in comparison to the existing techniques.

Original languageEnglish
Pages (from-to)284-293
Number of pages10
JournalDecision Support Systems
Issue number1
Publication statusPublished - Dec 2011
Externally publishedYes


  • Apparel retailing
  • Association mining
  • Data mining
  • Inductive decision trees
  • Negative association
  • Retail data

ASJC Scopus subject areas

  • Management Information Systems
  • Information Systems
  • Developmental and Educational Psychology
  • Arts and Humanities (miscellaneous)
  • Information Systems and Management


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