5 Conclusion Together with the rapi

5 Conclusion Together with the rapid development of database technology and network communication technology, overwhelming libraries in colleges and universities have realized the transformation from traditional manual service mode to computer automatic processing mode. For further improving the information degree of library management, the thesis studies library management data mining in colleges and universities with the improved algorithm based on collaborative filtering association rules. The thesis elaborately introduces how to adopt the association rules and collaborative filtering mining algorithm to carry out information mining for book borrowing records in the library. Moreover, based on the real borrowing records in the library where the author works, the thesis designs a proper book recommendation system with the user-based and book-based collaborative filtering technology, excavates the association of readers’ borrowing preferences and the association of books and ultimately derives readers’ borrowing rules. In this way, the system realizes the personalized book recommendation functions in favor of readers. Finally, the thesis assesses the effectiveness and predictability of the recommendation system through the test and derives the conclusion that book-based collaborative filtering algorithm has much higher prediction success ratio (precision ratio) than user-based collaborative filtering algorithm. It has certain referential values to the book recommendation work in the library.