Research Article
Research on Shopping Mall Sales Based on Apriori Association Rule Mining Algorithm
@INPROCEEDINGS{10.4108/eai.28-10-2022.2328459, author={Quan Jiang and Ming-le Ma and Liang-yu Dong}, title={Research on Shopping Mall Sales Based on Apriori Association Rule Mining Algorithm}, proceedings={Proceedings of the International Conference on Financial Innovation, FinTech and Information Technology, FFIT 2022, October 28-30, 2022, Shenzhen, China}, publisher={EAI}, proceedings_a={FFIT}, year={2023}, month={4}, keywords={mall sales; association rule mining; the apriori algorithm; correlation analysis}, doi={10.4108/eai.28-10-2022.2328459} }- Quan Jiang
Ming-le Ma
Liang-yu Dong
Year: 2023
Research on Shopping Mall Sales Based on Apriori Association Rule Mining Algorithm
FFIT
EAI
DOI: 10.4108/eai.28-10-2022.2328459
Abstract
The placement of goods in a shopping mall may seem insignificant, but in fact it has a significant impact on sales and customer experience. In order to improve the sales of goods in shopping mall, taking the sales data set of shopping malls as the research object, the Apriori algorithm based on association rule mining is used to carry out association analysis on the sales data of shopping malls, and the algorithm model is established according to the minimum support and minimum confidence. Comprehensive analysis of which goods should be adjusted to increase sales and improve customer happiness index. Experimental results show that the Apriori algorithm is used to analyze the results, compared with the original display of goods, the probability of customers to buy naturally increases by about 300%. The application of the model provides a solution for the shopping mall to improve sales and improve customer experience.
