【摘要】 在大数据背景下，从传统图书馆到智慧图书馆，图书资源呈指数级增长。随着馆藏图书资源的增加，读者在选取图书时愈发凸显出“选择困难症”的问题，找不到需要的图书资源。图书馆只有更了解读者，才不至于让海量的图书资源长期只存储在设备中休眠。文章设计的图书推荐系统是基于用户画像的个性化推荐系统，是在协同过滤等算法的基础上，结合用户的画像信息，来更精准地推荐书籍和提供服务。该系统通过收集用户静态数据，挖掘用户的动态数据，分析用户行为，进而实现图书精确推荐，提高图书资源的利用率。更多还原

【Abstract】 In the context of big data, book resources are growing exponentially from traditional libraries to smart libraries. With the increase of library resources, readers are increasingly facing the problem of “selection difficulties” when selecting books, and are unable to find the necessary book resources. Only by gaining a better understanding of readers can libraries prevent massive book resources from being stored in devices for a long time. The book recommendation system designed in the article is a personalized recommendation system based on user profiles. It combines collaborative filtering and other algorithms with user profile information to more accurately recommend books and provide services. This system collects static user data, mines dynamic user data, analyzes user behavior, and achieves precise book recommendation, improving the utilization rate of book resources.更多还原