基于概率矩阵分解的馆藏数字资源智能推荐方法研究

Research on the Intelligent Recommendation Method of Digital Resources of Library Collection Based on Probabilistic Matrix Factorization

文章将概率矩阵分解方法应用于馆藏数字资源的智能推荐之中,研究了基于概率矩阵分解的馆藏数字资源智能推荐方法。实验结果表明,该方法能够显著提高馆藏数字资源的推荐效果,有助于提升馆藏数字资源的利用效率与图书馆信息服务的水平与用户满意度。

This paper applies probabilistic matrix factorization method to the intelligent recommendation of digital resources of library collection as well as researches on the intelligent recommendation method of digital resources of library collection based on probabilistic matrix factorization. The experimental results show that this method can significantly improve the recommendation effect of digital resources of library collection, which contributes to the utilization efficiency of digital resources of library collection, library information service level and user satisfaction.