Study on Library Management System Based on Data Mining and Clustering Algorithm
Jing Wang, Roobaea Alroobaea, Abdullah M Baqasah, Anas Althobaiti, Lavish Kansal
In order to improve the information retrieval and resource sharing abilities of the library and establish an intelligent library information management system, alibrary management system based on data mining and clustering algorithm is proposed. The system development is divided into two modules: library mining algorithm design and information management system software development. Library data mining design and clustering algorithm of library management system development. System development is divided into two modules: library mining algorithm design and information management system software development. Big data fusion and feature clustering methods is used to design intelligent information retrieval algorithms in library information management to establish library management database. Realizing the development and design of library management system under embedded environment, and finally experimental test analysis is carried out. Results show that the use of the proposed method for library information management can improve the accuracy of book recommendation, which is 16.7% higher than traditional methods on average. It has good data mining, and has good performance indicators in data recall and precision. Therefore, this algorithm is not only a means of automated management of library systems, but also an effective means to realize library information modernization.
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