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Association Rules Mining on Retail Data

Author

Listed:
  • Hatice Dağaslanı

    (İstanbul Commerce University, Natural and Applied Sciences, Department of Statistics, Istanbul, Turkiye.)

  • Özlem Deniz Başar

    (İstanbul Commerce University, Graduate School of Natural and Applied Sciences, Department of Statistics, İstanbul, Türkiye.)

Abstract

The development in information technologies, artificial intelligence, and data mining benefits people in many areas. With this development, data stacks are formed through the storage of ever-increasing data. Accessing useful information from the data heaps is a very difficult process. This has led to the emergence and development of the concept of data mining. In this study, the relationship between the categories of the products sold by a company in the retail sector operating in Turkey was analyzed using the Apriori algorithm, which is an algorithm used in data mining. In the application, one-day sales data of the company was used. The data obtained was provided to extract the association rules with the help of Python. In this way, the purchasing habits of customers were determined by finding meaningful relationships between products using association rules.

Suggested Citation

  • Hatice Dağaslanı & Özlem Deniz Başar, 2022. "Association Rules Mining on Retail Data," EKOIST Journal of Econometrics and Statistics, Istanbul University, Faculty of Economics, vol. 0(37), pages 199-211, December.
    • Handle: RePEc:ist:ekoist:v:0:y:2022:i:37:p:199-211
    DOI: 10.26650/ekoist.2022.37.1145052
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