• Kalyan Paik

The digital transformation of libraries is reshaping how they serve users, with a growing emphasis on personalized information services (PIS) that cater to individual preferences, behaviors, and needs. As users increasingly expect tailored experiences similar to those offered by commercial platforms like Netflix, libraries are adapting by leveraging advanced technologies such as artificial intelligence (AI), machine learning, and behavioral analytics. These innovations enable libraries to provide customized recommendations, learning pathways, and dynamic content delivery, ensuring that users receive relevant and timely information. This paper explores how libraries can implement personalization strategies inspired by Netflix’s recommendation engine to enhance user engagement, improve information discovery, and create more responsive learning environments. While the benefits of personalized services are clear—ranging from increased user satisfaction and engagement to more efficient resource utilization—libraries must also address challenges such as privacy concerns, algorithmic biases, and the digital divide. To remain equitable and effective, libraries must prioritize ethical data use, ensure inclusivity in their offerings, and overcome technological constraints. This paper offers insights into the practical and ethical considerations of implementing personalized library services and provides a framework for libraries aiming to navigate the evolving digital landscape while enhancing the user experience.

Personalized Library Services, User Experience Enhancement, recommendations Technology, User centric Information.

"Personalized Information Services: The Netflix Model for libraries", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 3, page no.l405-l409, March-2024, Available :http://www.jetir.org/papers/JETIR2403B45.pdf

"Personalized Information Services: The Netflix Model for libraries", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 3, page no. ppl405-l409, March-2024, Available at : http://www.jetir.org/papers/JETIR2403B45.pdf