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Journals / Ekoist: Journal of Econometrics and Statistics / 2022 / Sayı: 37

Association Rules Mining on Retail Data

Hatice DAĞASLANI
Özlem DENİZ BAŞAR
Pages
199–211
Publication Date
2022-12-29
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

In this way, the purchasing habits of customers were determined by finding meaningful relationships between products using association rules.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The development in information technologies, artificial intelligence, and data mining benefits people in many areas.
📊
Key Findings & Data:With this development, data stacks are formed through the storage of ever-increasing data.
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Conclusion & Impact:In this way, the purchasing habits of customers were determined by finding meaningful relationships between products using association rules.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Apriori Algorithm · Association Rules Analysis · Data Mining

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.

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Cite This Article

DAĞASLANI, H., BAŞAR, Ö. D. (2022). Association Rules Mining on Retail Data. Ekoist: Journal of Econometrics and Statistics, Sayı: 37, 199–211. https://ajindex.com/articles/877103

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