基于矩阵分解的养老文化产品推荐

Recommendation of Aging Culture Products Based on Matrix Factorization

随着社会的进步和科学技术的发展,我国人口老龄化的速度不断加快,老龄人口的数量随之增长,并催生出了大量的养老文化产品。老年人如何在众多繁杂的信息中寻找到合适的养老文化产品,成为企业所面临的一个现实性问题。建立个性化推荐系统不仅能为目标群体提供符合他们需求的信息,满足其兴趣爱好,同时可以为企业标记目标客户,有助于提高企业推广的准确度。因此,运用矩阵分解算法建立养老文化产品推荐模型,对老年用户特征进行判断,并融入用户偏好这一因素提升推荐的准确度。最后通过实证分析进一步检验方法的有效性。

With the development of science and the advancement of society,the speed of population agingin China has been accelerating,the number of elderly people has increased and a large number of old-agecultural products have come into being.How to find suitable cultural products in the vast amount of in-formation for the elderly has become a realistic problem for enterprises.Establishing apersonalized rec-ommendation system not only provides the target group with information meeting their needs,but alsomeets their interests and hobbies.Mean while,it can mark the target customers for the company and helpto improve the accuracy of the company promotion.This paper uses matrix decomposition algorithm toestablish a recommendation model of aging culture products,judges the characteristics of the elders,andintegrates the factors of user preference to improve the accuracy of recommendation.Finally,the effec-tiveness of the method is further tested by empirical analysis.