Product Mentor – Sentiment Based Product Recommender With Chatbot: An Experimental Study

Product Mentor is a cutting-edge platform designed to simplify the process of choosing the right products using sophisticated sentiment analysis and Natural Language Processing (NLP) techniques. The system gathers and interprets user feedback from a variety of sources, sorting it into positive, negative, or neutral categories. This sentiment-focused evaluation enables the platform to provide customized product recommendations based on each user’s preferences, allowing them to swiftly discover the most suitable products. An interactive chatbot is available, offering real-time assistance and helping users navigate the recommendation system effectively. Beyond sentiment analysis, Product Mentor delivers in-depth product information, including specifications and user reviews, ensuring well-informed choices. By combining sentiment insights with detailed product data, the platform offers a comprehensive perspective on products, improving user satisfaction and streamlining the buying experience across diverse product categories. The platform’s intelligent recommendation engine, along with its real-time support and intuitive interface, ensures a seamless, engaging, and personalized shopping journey.

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Publication Details

Journal
Premier journal of science.
Published
2026-01-14
DOI
https://doi.org/10.70389/pjs.100218
Primary Topic
Sentiment Analysis and Opinion Mining
Type
article
Field-Weighted Citation Impact
0.00
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article

Product Mentor – Sentiment Based Product Recommender With Chatbot: An Experimental Study

Ajith Kuriakose Mani, Sabari Kamalesan, Gokulnath Ayyapan, Mathivanan Purushothaman
Premier journal of science.
Sentiment Analysis and Opinion Mining
article

Product Mentor – Sentiment Based Product Recommender With Chatbot: An Experimental Study

Ajith Kuriakose Mani, Sabari Kamalesan, Gokulnath Ayyapan, Mathivanan Purushothaman
article en

Abstract

Product Mentor is a cutting-edge platform designed to simplify the process of choosing the right products using sophisticated sentiment analysis and Natural Language Processing (NLP) techniques. The system gathers and interprets user feedback from a variety of sources, sorting it into positive, negative, or neutral categories. This sentiment-focused evaluation enables the platform to provide customized product recommendations based on each user’s preferences, allowing them to swiftly discover the most suitable products. An interactive chatbot is available, offering real-time assistance and helping users navigate the recommendation system effectively. Beyond sentiment analysis, Product Mentor delivers in-depth product information, including specifications and user reviews, ensuring well-informed choices. By combining sentiment insights with detailed product data, the platform offers a comprehensive perspective on products, improving user satisfaction and streamlining the buying experience across diverse product categories. The platform’s intelligent recommendation engine, along with its real-time support and intuitive interface, ensures a seamless, engaging, and personalized shopping journey.

Premier journal of science.
Thai-Nichi Institute of Technology (TH)
Openalex Percentile: Top 81%
Sentiment Analysis and Opinion Mining
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