Library Recommendation System
DOI:
https://doi.org/10.53555/jaz.v44iS8.3554Keywords:
Recommendation system, Books recommendation, Library, Machine learningAbstract
Nowadays, the majority of online book retailers utilize their own recommendation engines to suggest books to their customers. Nonetheless, the majority of the times, the books that are suggested to users are irrelevant. This system aims to create a new strategy by utilizing the content-based filtering capability. This technique will result in a more refined and useful recommendation for the user. For testing reasons, a web-based prototype will be developed, and the system will be taught by feeding it data. Users will benefit from our recommendation system by having easier access to library materials and reduced resource waste.
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