JOURNAL ARTICLE

Association Rules Mining on Retail Data

Hatice DağaslanıÖzlem Deniz Başar

Year: 2022 Journal:   Ekoist Journal of Econometrics and Statistics Vol: 0 (0)Pages: 0-0   Publisher: Istanbul University

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.

Keywords:
Association rule learning Apriori algorithm Purchasing Python (programming language) Data mining Computer science Data science Retail sales Process (computing) Association (psychology) Business Marketing

Metrics

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FWCI (Field Weighted Citation Impact)
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Refs
0.18
Citation Normalized Percentile
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Topics

Data Mining Algorithms and Applications
Physical Sciences →  Computer Science →  Information Systems

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