协同过滤推荐算法的改进

Improvement of Collaborative Filtering Recommendation Algorithms

随着电子商务网站的快速发展,为了促进购物网站的发展和提高经济效益,吸引新客户并留住老客户成为一种有效的手段。因此,设计和实现高效的个性化推荐算法是各大网站最关注的技术之一。具体地,针对传统算法推荐准确度不高的问题,采用融合用户特征与协同过滤的方式对算法进行优化,以提高推荐的精准度。

With the rapid development of e-commerce websites,in order to promote the development of shopping websites and improve economic efficiency,attracting new customers and retaining old customers has become an effective means.Therefore,the design and implementation of efficient personalized recommendation algorithm is one of the most concerned technologies of major websites.Specifically,aiming at the problem of low recommendation accuracy of traditional algorithms,the algorithm is optimized by integrating user characteristics and collaborative filtering to improve the accuracy of recommendation.