Research on Library Collection Resource Recommendation Algorithm based on Deep Learning

With the continuous development of deep learning technology, deep learning algorithms have also been widely used in library resource recommendation. The deep learning algorithm has powerful feature extraction and classification capabilities, which can effectively solve the data sparsity and cold start problems of library resource recommendation. Therefore, this paper proposes a deep learning algorithm to evaluate and analyze the innovative recommendation algorithm. Firstly, natural language processing technology is used to evaluate book resources, and the indicators are divided according to the evaluation requirements of the recommendation algorithm to reduce the interference factors in the evaluation of the recommendation algorithm. Then, natural language processing technology evaluates the recommendation algorithm of library collection resources, forms a recommendation algorithm evaluation scheme, and comprehensively analyzes the evaluation results of the recommendation algorithm. MATLAB simulation shows that under certain evaluation criteria, the evaluation accuracy and evaluation time of the recommendation algorithm of library collection resources by the deep learning algorithm are better than those of the traditional recommendation algorithm.