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),