Digital Library Book Recommendation System Based on Tag Mining

Aiming at the problem of low utilization of library resources in the current network information-flooded environment, this paper designs a book recommendation system framework suitable for digital libraries. In the book recommendation system, the recommended candidate set of books is selected by using the reader’s borrowing record combined with the collaborative filtering model. Then, the book and the target reader are labeled. And the content similarity is calculated according to the content characteristics of the book and the reader’s comment information. Finally, the final recommendation result is obtained according to the calculation result and the library collection information. Providing book recommendation services in digital libraries can effectively help users enhance their reading interest and optimize the reader’s experience.