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DATA MINING TECHNIQUE TO FIND LOW-COST GROCERIES

📘 Volume 7 📄 Issue 5 📅 may 2022

👤 Authors

Amrutha B, Muthuramalingam B 1
1. Student, MCA, Sir M. Visvesvaraya Institute of Technology

📄 Abstract

An e-store, internet shop, web shop, online store, or virtual store is the physical equivalent of purchasing goods or services from a real business or shopping center. This is known as business-to-consumer (B2C) online shopping. The shopping cart project must design a shopping cart system to organize product data and other consumer information. When a customer adds a product to their cart, the algorithm compares data from other stores to find low-cost alternatives. Sentimental analysis is used to determine the pricing of the items in the cart. It compares the prices of each product across different stores and delivers a result that allows you to acquire everything for a low price. The data is evaluated using the Naive Bayes classifier, which looks at each product in the dataset and assesses if it is being purchased at a low cost.

🏷️ Keywords

Naive Bayes classifier Sentimental analysis Low-cost prediction.

📚 How to Cite:

Amrutha B, Muthuramalingam B , DATA MINING TECHNIQUE TO FIND LOW-COST GROCERIES , Volume 7 , Issue 5, may 2022, EPRA International Journal of Research & Development (IJRD) ,

🔗 PDF URL

https://cdn.epratrustpublishing.com/article/938pm_67.EPRA JOURNALS 10404.pdf

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