Sukhmanpreet Singh Hundal, Sahil Shukla, Baburao Konuri, Imran Ansari, Dr. Soumitra Das
Keywords:
PRS, sentiment analysis, natural language processing, user friendly, businesses
Abstract
The rapid growth of e-commerce platforms has necessitated efficient and reliable systems for product reviews, facilitating informed consumer decisions and fostering trust between buyers and sellers. This research paper presents a comprehensive analysis and design of a product review system tailored to meet the evolving needs of online consumers and businesses. The proposed system integrates advanced features such as sentiment analysis, user authentication, and review moderation to enhance the credibility and usefulness of reviews while addressing challenges such as fake reviews and spam. Advanced natural language processing and sentiment analysis techniques are integrated into the system, offering in-depth insights from user reviews. Furthermore, PRS goes beyond the basic review process, offering review of products to users based on their preferences, fostering engagement and loyalty. A user-friendly interface ensures that both posting reviews and engaging with other consumers is a seamless experience. Through this research, we aim to contribute to the advancement of e-commerce platforms by offering insights and solutions for optimizing the product review process, ultimately enriching the online shopping experience for consumers and fostering sustainable growth for businesses.
Article Details
Unique Paper ID: 164560
Publication Volume & Issue: Volume 10, Issue 12
Page(s): 1521 - 1524
Article Preview & Download
Share This Article
Join our RMS
Conference Alert
NCSEM 2024
National Conference on Sustainable Engineering and Management - 2024