A Personalized Recommender System Based on Library Database

Abstract

In recent years, the university libraries in China have acquired increasingly abundant electronic resources. However, the information silo phenomenon appears due to the lack of connection between university IT system and the community. Based on the book borrowing, favourite collection, comments and social relationship of students, this paper digs into the personalized interests of students, and promotes the design and implementation of a personalized recommender system. Specifically, the overall framework and recommender engine of the system were created based on the library data services. The modules in the system were also elaborated, and the recommendation results were verified by an offline test.