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<p>In this paper, after analyzing the structural system of the digital resource sharing model in colleges and universities, a shared storage model based on cloud storage is designed, and a digital teaching resource management and sharing platform for colleges and universities based on cloud storage is constructed on this basis. In order to realize accurate sharing, the sharing behaviors of teaching resources are symbolically illustrated, double behavior aggregation is performed, and a multidimensional preference personalized recommendation algorithm, i.e., DB-CGAT model, is designed to construct the personalized sharing module of teaching resources that integrates the behavioral graph. In addition, three types of experiments are conducted on the personalized sharing module of the platform to test its sharing performance and overall performance. The results show that the accuracy of this model is reduced by 0.04 compared with the traditional algorithm; the 90 percent time of login transaction is 2.44, and the time of query transaction is 1.46, which is all up to the standard value. All the action actions are green, and the number of clicks and throughputs in 5~30ss are around 120. Universities can benefit from the digital teaching resource management and sharing platform designed in this paper, which can improve teaching efficiency.</p>
</abstract>

In this paper, after analyzing the structural system of the digital resource sharing model in colleges and universities, a shared storage model based on cloud storage is designed, and a digital teaching resource management and sharing platform for colleges and universities based on cloud storage is constructed on this basis. In order to realize accurate sharing, the sharing behaviors of teaching resources are symbolically illustrated, double behavior aggregation is performed, and a multidimensional preference personalized recommendation algorithm, i.e., DB-CGAT model, is designed to construct the personalized sharing module of teaching resources that integrates the behavioral graph. In addition, three types of experiments are conducted on the personalized sharing module of the platform to test its sharing performance and overall performance. The results show that the accuracy of this model is reduced by 0.04 compared with the traditional algorithm; the 90 percent time of login transaction is 2.44, and the time of query transaction is 1.46, which is all up to the standard value. All the action actions are green, and the number of clicks and throughputs in 5~30ss are around 120. Universities can benefit from the digital teaching resource management and sharing platform designed in this paper, which can improve teaching efficiency.

Research on the Design of Digital Teaching Resource Management and Sharing Platform in Colleges and Universities Based on Cloud Storage

Capital University of Economics and Business

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

In this paper, after analyzing the structural system of the digital resource sharing model in colleges and universities, a shared storage model based on cloud...

Research on the Design of Digital Teaching Resource Management and Sharing Platform in Colleges and Universities Based on Cloud Storage

Pubblicato online: 13 dic 2023

Pagine: -

Ricevuto: 24 feb 2023

Accettato: 23 giu 2023

DOI: https://doi.org/10.2478/amns.2023.2.01480

Parole chiave
Cloud storage, Dual behavioral aggregation, DB-CGAT model, Personalized sharing, Management sharing platforms

© 2023 Yajie Wang, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Research on the Design of Digital Teaching Resource Management and Sharing Platform in Colleges and Universities Based on Cloud Storage

Pubblicato online: 13 dic 2023

Pagine: -

Ricevuto: 24 feb 2023

Accettato: 23 giu 2023

DOI: https://doi.org/10.2478/amns.2023.2.01480

Parole chiaveCloud storage, Dual behavioral aggregation, DB-CGAT model, Personalized sharing, Management sharing platforms

© 2023 Yajie Wang, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Parole chiave
Cloud storage, Dual behavioral aggregation, DB-CGAT model, Personalized sharing, Management sharing platforms