Because of the intensive usage of database systems, the university library has gathered a mass-circulation historical data. We employed data mining algorithms to reveal useful information in the investigation of circulation data. The book recommender system described in this work provides clients with book recommendations based on an apriori algorithm and association rules applied to transactional data. A web application is introduced and used to provide readers with recommendation information. Bookstores, information retrieval systems, and network reference databases can all benefit from the recommendation model.