Design of Information Service System of University Smart Library Based on Cloud Computing Technology

In order to better serve users, understand and meet users' needs, and provide personalized and refined services, the library has introduced the concept and technology of cloud computing into the construction of smart libraries, and has applied it to the intelligent service field of libraries. In the face of massive digital resources, using cloud computing technology can recommend digital resources to users more intelligently and efficiently. In this paper, collaborative filtering algorithm based on cloud computing is applied to the smart recommendation service of university smart library. According to the characteristics of reader users in university library, a reader feature model is constructed to generate candidate nearest neighbor sets, so as to generate nearest neighbor sets and recommendation results, so that the recommendation results can better match the preferences of readers, improve the accuracy of recommendation results, and provide algorithm support for building smart recommendation of university smart library. The experimental results show that the combination of the two methods can effectively adapt to the recommendation system with lower sparsity, better scalability and lower time complexity than the traditional collaborative filtering recommendation algorithm. The algorithm can recommend books for smart libraries efficiently and intelligently, and can meet the needs of smart libraries.