With the increase of library collections, it is difficult for readers to quickly find the books they want when choosing books. Book recommendation system is becoming more and more important. Based on the previous research, this paper proposes a book recommendation algorithm based on collaborative filtering and interest. Take the interest of the book itself as an important measurement index, including the number of searches, borrowing time, borrowing times, borrowing interval, and renewal times. Through the analysis of MAE and RMSE experiments, the results show that the method proposed in this paper converges faster than the traditional method.

中文翻译：

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基于协同过滤和兴趣度的图书推荐算法研究

随着图书馆馆藏量的增加，读者在选书时很难快速找到自己想要的书。图书推荐系统变得越来越重要。本文在前人研究的基础上，提出了一种基于协同过滤和兴趣的图书推荐算法。以图书本身的兴趣度作为重要的衡量指标，包括搜索次数、借阅次数、借阅次数、借阅间隔、续借次数等。通过对MAE和RMSE实验的分析，结果表明本文提出的方法比传统方法收敛速度更快。