PERSONALIZATION IN E-COMMERCE: ANALYZING AI ALGORITHMS FOR ENHANCED RECOMMENDATION ACCURACY AND CUSTOMER SATISFACTION

Registration ID: IJNRD_302443

Published ID: IJNRD2412127

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YAZIDU MALAM USMAN, ABUBAKAR SADIQ NASIHA, ABUBAKAR NAZIR, Ms. Anjali Goswami

Keywords— Artificial Intelligence (AI), E-commerce, Recommendation Systems, Personalization, Machine Learning, Collaborative Filtering, Content-based Filtering, Hybrid Recommendation Models.

Abstract— E-commerce is undergoing a significant transformation due to the rapid advancement of Artificial Intelligence (AI), particularly in the realm of personalized and efficient recommendation systems. These AI-powered systems process vast amounts of user information, including browsing patterns, purchasing habits, and personal characteristics, to offer customized product suggestions that boost customer contentment and loyalty. This study delves into the progression of AI in e-commerce recommendations, emphasizing methods such as collaborative filtering, content-based filtering, and hybrid models that integrate various approaches to enhance accuracy. Moreover, the research examines several key AI-driven algorithms frequently employed in recommendation systems, as each contributes unique strengths in analysing user data and forecasting preferences. These algorithms include decision trees, neural networks, matrix factorization, and clustering techniques. The paper also investigates the effects of these AI methodologies on user engagement, sales conversion, and overall business performance. Additionally, it addresses critical challenges like the cold start problem, where limited information about new users or products hinders recommendation accuracy, as well as ethical issues concerning data privacy and algorithmic bias. Through a comprehensive examination of AI's function in contemporary recommendation systems, this study aims to provide a thorough understanding of how AI is revolutionizing e-commerce and potential future advancements in this field.

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YAZIDU MALAM USMAN, ABUBAKAR SADIQ NASIHA, ABUBAKAR NAZIR, & Ms. Anjali Goswami (December-2024). PERSONALIZATION IN E-COMMERCE: ANALYZING AI ALGORITHMS FOR ENHANCED RECOMMENDATION ACCURACY AND CUSTOMER SATISFACTION. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(12), b275-b282. https://ijnrd.org/papers/IJNRD2412127.pdf

Volume 9 Issue 12, December-2024

Pages : b275-b282

Paper Reg. ID: IJNRD_302443

Published Paper Id: IJNRD2412127

Research Area: Science and Technology

Author Type: Indian Author

Country: raipur chhattisgarh, chhattisgarh, India

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