| 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 | |
| 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 |