A Comparative Study of Various Book Recommendation Algorithms for Public Libraries

Abstract

ABSTRACT Book recommendation algorithms in public libraries can recommend catalogs based on users’ borrowing records to assist in book retrieval. This paper introduced two recommendation algorithms, collaborative filtering and association rule, combined them into a hybrid recommendation algorithm, and conducted simulation experiments on the three recommendation algorithms. The results showed that the hybrid recommendation algorithm gave more personalized and specific recommendation results; the recommendation accuracy of the hybrid recommendation algorithm was higher than that of the other two algorithms regardless of the book borrowing volume of target users.