JOURNAL ARTICLE

Sentiment Based Product Recommendation System for E-Commerce Using Machine Learning Approaches

Muzakkiruddin Ahmed Mohammed

Year: 2022 Journal:   International Journal of Innovative Research in Computer Science & Technology Vol: 10 (6)Pages: 120-137

Abstract

Today, e-commerce is a thriving industry. We do not need to approach every customer to accept their orders here. A business creates a website to offer things to clients, who can then purchase the stuff they need within the same website. These e-commerce firms include well-known ones like Amazon, Shopify, Myntra, Flipkart, and Ajio. To create a product recommendation system for the end customers, we will be using the data set of e-commerce product reviews in this final project. A sentiment analysis model will be used to enhance the suggestions. Under this final project, we will develop a sentiment analysis engine utilising a variety of machine learning approaches before selecting the model that produces the best results.

Keywords:
Thriving Product (mathematics) Computer science E-commerce Sentiment analysis Variety (cybernetics) Recommender system Set (abstract data type) World Wide Web Data science Artificial intelligence

Metrics

1
Cited By
0.20
FWCI (Field Weighted Citation Impact)
11
Refs
0.56
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Sentiment Analysis and Opinion Mining
Physical Sciences →  Computer Science →  Artificial Intelligence

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