当前人工智能、区块链、大数据等技术掀起了第四次工业革命，新冠疫情的长期性加速了数字化、智能化应用的 推广，大数据加大了人们快速获取需求的难度，因而推荐系统得到广泛应用。推荐系统在图书领域也得到主流电商平台的应 用，通过基于Mahout框架的协同过滤推荐算法结合知识分类及用户兴趣提出了基于知识分类和用户兴趣的协同过滤推荐算 法，通过实验分析，算法提供了更加精细的个性化推荐和更高的推荐质量

At present, artificial intelligence, block chaining, big data and other technologies set off the fourth industrial revolution. The persistence of COVID-19 has accelerated the promotion of digital and intelligent applications, and the big data has increased the difficulty of people's rapid access to demand, thus the recommendation system has been widely applied. The recommendation system has also been applied in the mainstream e-commerce platform in the book field. In this paper, through the collaborative filtering recommendation algorithm based on Mahout framework, combined with knowledge classification and user interest, a collaborative filtering recommendation algorithm based on knowledge classification and user interest is proposed. Through experimental analysis, the algorithm provides more refined personalized recommendation and higher recommendation quality.