Research on Personalized Book Recommendation Model for New Readers

Abstract

In recent years, with the improvement of computing level, it is possible to provide personalized recommendation lists for users based on user behavior. Increasing number of books in library in university has an urgent demand for personalized book recommendation. A model is established by author using collaborative filtering algorithm, and targeting students who have never borrowed books from the library. The model generates the book recommendation lists for the target users by using their course selection records and existing borrowing data of known users. Finally, the paper compares the effects of different parameters setting in the algorithm.