Personalized library model adapts book recommendations to readers' changing knowledge

University libraries hold vast collections of scholarly work, yet most academic books are borrowed only a handful of times each year. A study published in the International Journal of Information and Communication Technology suggests that the problem lies less in library logistics than in the lack of a sophisticated recommendation system available to readers. The team behind the research have come up with a new approach to library recommendation systems that replaces the static models with an approach that adapts to the readers' changing learning needs.