Reading helps people focus, remember things better, be more empathetic, and communicate more effectively. It can lengthen the human’s life, lessen stress, and enhance mental wellness. It also expands the reader’s vocabulary and improves writing skills as well. During the most recent couple of many years, with the ascent of YouTube, Instagram, Facebook, Amazon, Netflix, and numerous other such web services, recommender systems have assumed increasingly more position in our lives. Some readers might spend a lot of time surfing the internet looking for more similar books when they enjoy a book with new insights. Recommender systems are now-a-days a part of everything we do online, from e-commerce to advertising. Therefore, the primary goal of the proposed work is to propose an AI based collaborative filtering approach to prescribe relevant books to the readers in light of prevalence and the reader’s interests. This platform helps to find the books to read next.
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1 April 2025
INTERNATIONAL CONFERENCE ON GREEN COMPUTING FOR COMMUNICATION TECHNOLOGIES (ICGCCT – 2024)
6–7 March 2024
Salem, India
Research Article|
April 01 2025
Book recommendation system: An AI companion for curated book suggestions Available to Purchase
Aruna Subramanian;
Aruna Subramanian
a)
a)Corresponding Author: [email protected]
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Srinivasa Boopathy Senthil Kumar;
Srinivasa Boopathy Senthil Kumar
c)
Search for other works by this author on:
Aruna Subramanian
a)
Yokesh Durairaj
b)
Srinivasa Boopathy Senthil Kumar
c)
Hariharan Saravanan
d)
a)Corresponding Author: [email protected]
AIP Conf. Proc. 3279, 020199 (2025)
Citation
Aruna Subramanian, Yokesh Durairaj, Srinivasa Boopathy Senthil Kumar, Hariharan Saravanan; Book recommendation system: An AI companion for curated book suggestions. AIP Conf. Proc. 1 April 2025; 3279 (1): 020199. https://doi.org/10.1063/5.0263396
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