ASSOCIATION RULES MINING USING APRIORI ALGORITHM, SUPPORT FOR SALES ACTIVITIES IN SUPERMARKET

Trần Thị Xuân; Nguyễn Văn Núi

doi:10.34238/tnu-jst.5122

ASSOCIATION RULES MINING USING APRIORI ALGORITHM, SUPPORT FOR SALES ACTIVITIES IN SUPERMARKET

About this article

Received: 07/10/21 Revised: 15/11/21 Published: 15/11/21

Authors

1. Tran Thi Xuan , TNU - University of Economics and Business Administration
2. Nguyen Van Nui, TNU - University of Information and Communication Technology

Abstract

Currently, data mining is gaining popularity in the retail sector and is an effective analytical method for detecting useful and unknown information in retail data. The organization of goods and related business activities towards enhancing the customer satisfaction is one of the very important jobs. This study will focus on analyzing, mining and finding association rules based on past data, thereby proposing some recommendations to support the business operation of the supermarket to be more optimized. For example, if a supermarket wants to arrange its stores in the most reasonable way, they can look at the purchase history and arrange the sets of products that are often bought together into one store. Or a news website that wants to introduce users to the most related articles, the same rule can be applied. In this paper, we calculate and analyze the relationship between products to help a supermarket arrange reasonable items for customers to buy goods by using association rule mining algorithm Aprori.

Keywords

Data mining; Association rule mining; Association rule; Apriori; Sale activity

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DOI: https://doi.org/10.34238/tnu-jst.5122

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