Enhanced E-Commerce Personalization with a Chatbot-Based Product Recommendation Algorithm

Authors

  • Dr. Darshana Desai

Keywords:

E-commerce personalization, chatbots, machine learning, natural language processing, hybrid recommendation systems, collaborative filtering, content-based filtering, reinforcement learning, multimodal AI, emotion-aware systems.

Abstract

The rapid expansion of e-commerce has profoundly influenced consumer behavior and expectations, drivingthe need for intelligent, highly personalized shopping experiences. Artificial intelligence (AI), particularlyin the form of conversational chatbots, has emerged as a transformative tool enabling real-time, contextual,and adaptive product recommendations. 

References

Adamopoulou, E., & Moussiades, L. (2020). An overview of chatbot technology. AI & Society, 35(3),

–391. https://doi.org/10.1007/s00146-020-00958-5

Bobadilla, J., Ortega, F., Hernando, A., & Gutiérrez, A. (2013). Recommender systems survey.

Knowledge-Based Systems, 46, 109–132. https://doi.org/10.1016/j.knosys.2013.03.012

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Published

2024-10-21

How to Cite

Dr. Darshana Desai. (2024). Enhanced E-Commerce Personalization with a Chatbot-Based Product Recommendation Algorithm. Journal of Computational Analysis and Applications (JoCAAA), 33(07), 2226–2234. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/3145

Issue

Vol. 33 No. 07 (2024): JOCAAA

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.