Design of classification management platform of university digital teaching resources under the background of artificial intelligence
In order to solve the problems of poor selection effect and long resource classification time in existing platform design,a design of a digital teaching resource classification management platform for universities under the background of artificial intelligence is proposed.The article uses artificial intelligence technology to optimize the resource classification process.In terms of hardware design,the central processing unit(CPU)is used as the core,combined with multidimensional scaling(MDS)registers and a three-level single cycle routing controller to optimize memory address arrangement,and integrate components such as random access memory(RAM)to achieve real-time data communication through bus probes.In terms of software design,a weighted grid algorithm is used to calculate resource distribution and cluster resources.The platform architecture is based on cloud platforms and mobile devices,achieving classification,coding,and management of resource data.Using knowledge graph structure for resource retrieval to improve management efficiency.The test results show that the success rate of resource selection reaches 95%,and the classification time is shortened to within 125 seconds,significantly improving the convenience of resource updates and maintenance.
万方数据
维普
