基于云计算和深度信念网络的数字资源配置

针对当前高校图书馆数字资源配置存在合理性差和效率低等问题，提出一种基于云计算和深度信念网络的图书馆数字资源配置方法。首先采用云计算技术构建图书馆数字资源配置模型；其次采用深度信念网络对图书馆数字资源节点进行特征训练，并对资源进行合理配置；最后与图书馆数字资源配置的其他方法进行实验分析与比较。分析结果表明，所提方法既可提高图书馆数字资源配置的质量和效率，又可减少图书馆数字资源配置时间，效果更优。

Digital Resource Allocation Based on Cloud Computing and Deep Belief Network

Aiming at the problems of poor rationality and low efficiency in the allocation of digital resources in university libraries, this paper proposes a method of library digital resources allocation based on cloud computing and deep belief network. Firstly, the cloud computing technology is used to construct the model of library digital resource allocation. Secondly, the deep belief network is used to train the characteristics of library digital resource nodes, and reasonable resource allocation is carried out. Finally, the experimental analysis and comparison of library digital resource allocation with other methods are carried out. The analysis results show that the proposed method can not only improve the quality and efficiency of library digital resource allocation, but also reduce the time of library digital resource allocation.