Research on Resource Sharing Methods of English Translation Corpus in Colleges and Universities under the Background of Informatization
Published Online: Sep 26, 2025
Received: Jan 31, 2025
Accepted: May 09, 2025
DOI: https://doi.org/10.2478/amns-2025-1066
Keywords
© 2025 Wei Huang et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
The rapid development of informatization of educational resources provides great opportunities and impetus for the sharing of English translation corpus resources in colleges and universities. This paper proposes a teaching resource sharing scheme based on cloud computing, builds a cloud platform for English translation corpus resources, and provides new ideas for realizing English translation corpus resource sharing. The overall architecture of the cloud platform is designed from the infrastructure layer, platform layer and application layer, and the teaching resource recommendation algorithm and resource sharing algorithm based on immune-evolutionary algorithm are proposed respectively to realize the resource recommendation and sharing function of the cloud platform, and the corresponding performance testing experiments are carried out to test the effectiveness of the function. In the recommendation performance testing experiment of the cloud platform, the recommendation success rate of this paper’s recommendation algorithm in 100 experiments is as high as 99.6%, with a response speed of only 4.5s, and the recommendation success rate in 500 experiments still reaches 99.5%, which reflects the excellent performance of resource recommendation. In the sharing performance test, the posttest score of the experimental group applying the cloud platform for English translation teaching is higher than that of the control group by 2.76 points, and the mean values of the indicators of learning styles, learning interests, and attitudes and motivations in learning psychology are also higher than those of the control class by 14.53, 16.99, and 6.33, and the mean values of the indicators of psychic load are decreased significantly, all of which show significant differences (P<0.05).