Intelligent E-Commerce Chatbot for Personalized Product Recommendations Using Text Mining and Machine Learning

Innovative technology solutions have been developed in response to the growing need for effective and customized client contact on e-commerce platforms. This work introduces an intelligent chatbot system that uses machine learning and text mining techniques to improve user satisfaction and answer customer concerns. Advanced Natural Language Processing (NLP) models have been trained on large datasets, allowing for precise user intent interpretation and pertinent product recommendations. A strong recommendation engine is included into the system architecture to aid in decision-making, ultimately enhancing the customer experience by providing individualized, real-time help. The study also highlights the significance of data privacy by using privacy-preserving techniques to safeguard user data. The system’s scalability and performance benefits are highlighted through thorough comparisons with current models. By showcasing the useful uses of machine learning and text mining in enhancing customer contact and service delivery, this study makes a substantial contribution to the development of AI-driven solutions in e-commerce.

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Publication Details

Published
2024-11-28
DOI
https://doi.org/10.1109/icaiccit64383.2024.10912384
Primary Topic
FinTech, Crowdfunding, Digital Finance
Type
article
Field-Weighted Citation Impact
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article

Intelligent E-Commerce Chatbot for Personalized Product Recommendations Using Text Mining and Machine Learning

Adithya, Kavya Kavya, M. S. Minu, SreeRanjini
FinTech, Crowdfunding, Digital Finance
article

Intelligent E-Commerce Chatbot for Personalized Product Recommendations Using Text Mining and Machine Learning

Adithya, Kavya Kavya, M. S. Minu, SreeRanjini
article en

Abstract

Innovative technology solutions have been developed in response to the growing need for effective and customized client contact on e-commerce platforms. This work introduces an intelligent chatbot system that uses machine learning and text mining techniques to improve user satisfaction and answer customer concerns. Advanced Natural Language Processing (NLP) models have been trained on large datasets, allowing for precise user intent interpretation and pertinent product recommendations. A strong recommendation engine is included into the system architecture to aid in decision-making, ultimately enhancing the customer experience by providing individualized, real-time help. The study also highlights the significance of data privacy by using privacy-preserving techniques to safeguard user data. The system’s scalability and performance benefits are highlighted through thorough comparisons with current models. By showcasing the useful uses of machine learning and text mining in enhancing customer contact and service delivery, this study makes a substantial contribution to the development of AI-driven solutions in e-commerce.

SRM Institute of Science and Technology (IN)
Decent work and economic growth
Openalex Percentile: Top 55%
FinTech, Crowdfunding, Digital Finance
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