图书借阅是图书馆最基本的服务,根据用户的借阅爱好为其自动地推荐相关图书是解决图书借阅效率与可靠性等问题的关键。为了提高图书推荐的准确率,本文利用改进的K-mean算法对借阅用户的类别与偏好性进行了系统的分析,然后通过构造用户借阅偏好性矩阵与用户相似性度量,采用协同过滤算法实现了图书借阅的个性化推荐。实验结果表明,本文算法可根据用户的借阅爱好准确地为其推荐图书,整体上具有较高的性能。 Book lending is the most basic service of the library, according to the user’s borrowing preferences to automatically recommend related books is the key to solve the problem of efficiency and reliability of book lending. In order to improve the accuracy of book recommendation, this paper uses the improved K-mean algorithm to systematically analyze the types and preferences of borrowers, and then constructs the user-borrowing preference matrix and the similarity measure of users, and uses the collaborative filtering algorithm Personalized recommendation of book loan. The experimental results show that the proposed algorithm can accurately recommend books to users according to their borrowing preferences, and has a higher overall performance.