Exploration on Quick Response (QR) Code Behaviour in Commerce based Platforms Using Machine Learning

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Archana Uriti 1,* Surya Prakash Yalla 1

1. GMR Institute of Technology, Rajam, Andhra Pradesh, India

* Corresponding author.

DOI: https://doi.org/10.5815/ijieeb.2023.05.01

Received: 15 Mar. 2023 / Revised: 10 Apr. 2023 / Accepted: 4 May 2023 / Published: 8 Oct. 2023

Index Terms

Confusion matrix, QR code, Count vectorizer, GridsearchCV, Python Tkinter


The "rapid response" code, or QR code, is made to quickly decode vast amounts of data. Any managed device, such as a smartphone, is able to capture it, and it is simple to access simply scanning the 2D matrix code. The dataset is analyzed utilizing machine learning techniques, such as the confusion matrix score utilized for the multinomial naive Bayes algorithm's performance analysis. The QR code generation is limited to single product and is extended now to include all products. Due to its ability to provide clients with benefits including speedy, error-free access and the ability to store a lot of data. Generally, many people are using the online payment for any transaction for flexibility and one can do at any place at any time. For bulk or huge payment, cash is not a good option. Hence many retailers join in the e-wallet companies and make their payment so flexible and faster transaction. Because of these benefits, QR code has becoming widespread.

Cite This Paper

Archana Uriti, Surya Prakash Yalla, "Exploration on Quick Response (QR) Code Behaviour in Commerce based Platforms Using Machine Learning", International Journal of Information Engineering and Electronic Business(IJIEEB), Vol.15, No.5, pp. 1-12, 2023. DOI:10.5815/ijieeb.2023.05.01


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