Deducing Synthetic Reviews Using Gradient-Boosting Technique

Author(s)	Vijet Hegde, Yashwanth S, Vinay Kumar B K, Veeresh Mulimani, Dr.Nirmala S
Country	India
Abstract	This research explains a comprehensive system for detecting fake, computer-generated reviews on e-commerce platforms like Amazon and Flipkart. The proposed solution integrates a robust machine learning model, a scraping mechanism for collecting reviews, and a user-friendly frontend built with React. Using a novel ensemble method combining LightGBM, CatBoost, and XGBoost, alongside natural language processing (NLP) techniques, the system achieves high accuracy in separating genuine opinion from fake ones. This study aims to improve customer trust and maintain the integrity of online marketplaces.
Keywords	LightGBM,CatBoost,XGBoost,Puppeteer, spaCy, TextBlob ,Docker,API
Field	Engineering
Published In	Volume 6, Issue 6, November-December 2024
Published On	2024-12-31
DOI	https://doi.org/10.36948/ijfmr.2024.v06i06.34356
Short DOI	https://doi.org/g82gf3

About IJFMR Fees & Payment Current Issue Publication Archive	Submit Research Paper Track Submission Status Publication Guidelines Publication Ethics Peer Review & Plagiarism	Join as a Reviewer Editors & Reviewers Reviewer Referral Program Get Reviewer Membership Certi.	Website/Journal Policies Usage Policy Content Policies Privacy Policy

Contact Us		+91-9687-828-838	editor@ijfmr.com

International Journal For Multidisciplinary Research