Research on Library Queuing Model Based on Data Mining
Abstract
The current work of library circulation service desk is being transferred from traditional pure manual operations to human–machine collaboration and artificial intelligence. It is urgent to study a set of general and reliable service desk distribution models to better optimize staffing and improve service efficiency and quality. Based on the theory of queuing, the model for the optimization of distribution desks is explored, and the overall design of the plan is completed (sample data collection and mining, parameter estimation, operation index calculation, results analysis, and evaluation, etc.). In this case, the parameters were selected from Nanyuan library circulation service desk in Shanghai University of Medicine & Health Sciences. Based on actual statistical sampling, this article has estimated the feasibility, reliability, and effectiveness by a reasonable parameter-range verification scheme, provided a strong reference for the decision-making of library circulation departments, and effectively improved the efficiency of circulation services.
Keywords: queuing theory, data mining, stratified sampling
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