Approach to Kirana Store Product Arrangement Using Machine Learning
Ajita Patel, Krishna Kumar Tiwari
Asian Journal of Research in Computer Science · pp. 72–83 · Published 15 Sep 2021
10.9734/ajrcos/2021/v11i430271Abstract
Market Basket Analysis (MBA) is a method for determining the association between entities, and it has often been used to study the association between products in a shopping basket. Trained Computer vision models are able to recognize objects in photos so accurately that it can even outperform humans in some instances. This study shows that combining objective detection techniques with market basket analysis can assist Stores/Kirana in organizing the products effectively. With the use of MBA and Object detection, we formulated recommendations for store arrangements along with putting a recommendation engine on top to help shoppers. After deploying this to local Kirana stores, the Kirana store was able to see an increase of 7% in the sale. The recommendation engine performed better than just the domain knowledge of the kirana store.
Cited by 2
H. Hery, A. E. Widjaja · Journal of Digital Market and Digital Currency · 2024
Ishita Sajwan, Rajnee Tripathi · 2024 Sixth International Conference on Computational Intelligence and Communication Technologies (CCICT) · 2024
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