In the process of dynamic recommendation of refined performance evaluation information in hospitals,random dynam-ic variables are generated,which slows down the calculation speed of recommendation algorithms.To overcome this problem,a dynamic iterative sampling algorithm for hospital refined performance evaluation information dynamic recommendation is pro-posed.In a dynamic iterative sampling environment,the collected data are uniformly transformed into structured data,and the data dimensions are unified to calculate the dynamic changes in hospital performance evaluation information.Based on the calcu-lation results,the original project set is classified and processed to obtain multiple subsets.On this basis,the user information weight and the weight of performance information within the subsets are calculated,and the similarity between the two is calcu-lated based on the weight calculation result,and compose highly similar information into a recommendation information set,and use cloud computing technology to achieve dynamic recommendations for multiple users.Under the same number of iterations,the experimental results of the two common recommendation algorithms are compared and analyzed.The experimental results show that the proposed hospital performance evaluation information dynamic recommendation algorithm has fast convergence speed,short running time,high recommendation accuracy,which significantly improves overall computational performance.
维普
万方数据