Aggarwal, Ankur (2025) Evolution of recommendation systems in the age of Generative AI. International Journal of Science and Research Archive, 14 (1). pp. 485-492. ISSN 2582-8185
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Abstract
This article examines the transformative evolution of recommendation systems in the era of Generative AI, exploring how these advanced technologies have revolutionized user experience and business outcomes across digital platforms. The article investigates the transition from traditional rule-based approaches to sophisticated model-based systems, highlighting the impact of deep learning technologies, explainable AI mechanisms, and multimodal integration. Through comprehensive analysis of recent developments, the article demonstrates how Generative AI has enhanced personalization capabilities, improved recommendation accuracy, and enabled more contextually relevant suggestions while addressing crucial aspects of user privacy and system transparency. The article encompasses various domains, including e-commerce, content streaming, and digital marketplaces, offering insights into both technical advancements and practical implementations of modern recommendation systems.
Item Type: | Article |
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Official URL: | https://doi.org/10.30574/ijsra.2025.14.1.0061 |
Uncontrolled Keywords: | AI; Deep learning technologies; Accuracy; E-commerce |
Depositing User: | Editor IJSRA |
Date Deposited: | 13 Jul 2025 13:35 |
Related URLs: | |
URI: | https://eprint.scholarsrepository.com/id/eprint/548 |