Indexing Metadata

1 Title of the Article Sentiment Based Product Recommendation System for E-Commerce Using Machine Learning Approaches
2 Author's name Muzakkiruddin Ahmed Mohammed: B. Tech Scholar, Department of Electrical and Electronics Engineering, Lords Institute of Engineering and Technology, Hyderabad, India
3 Author's name
4 Subject Electrical and Electronics Engineering
5 Keyword(s) Recommender Systems; Logistic Regression and Analysis; Random Forest; Xgboost; Hyperparameter Tuning; Deployment.
6 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.

7 Publisher Innovative Research Publication
8 Journal Name; vol., no. International Journal of Innovative Research in Computer Science & Technology (IJIRCST); Volume-10 Issue-6
9 Publication Date November 2022
10 Type Peer-reviewed Article
11 Format PDF
12 Uniform Resource Identifier https://ijircst.org/view_abstract.php?title=Sentiment-Based-Product-Recommendation-System-for-E-Commerce-Using-Machine-Learning-Approaches&year=2022&vol=10&primary=QVJULTEwNjU=
13 Digital Object Identifier(DOI) 10.55524/ijircst.2022.10.6.20   https://doi.org/10.55524/ijircst.2022.10.6.20
14 Language English
15 Page No 120-137