Abstract
Aiming at the problems of low coverage of teaching resource recommendation results, long running time of the platform and low accuracy of Resource Recommendation in traditional methods, this paper designs an intelligent real-time news communication platform and applies it to education and teaching. The ia as + PAAS + SaaS standard three-tier cloud architecture is adopted to design the overall architecture of the platform, and the tracking and clustering of news is realized through the content acquisition and editing module, distributed news clustering module and news communication effect tracking module. TF-IDF algorithm is used for news data feature selection, and the feature correlation degree is calculated. According to the calculation results, a news communication data recommendation model based on the improved LDA model is established to realize the effective recommendation of resources. Finally, the designed platform is applied to practical teaching and its application effect is analyzed. The experimental results show that the resource recommendation accuracy of this method is high, up to 90%, the running time of the platform is always about 1.0 s, and the resources can cover more fields, basically up to 100%, which fully verifies its application value.
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Acknowledgements
This study is supported by scientific research project of colleges and universities in Inner Mongolia Autonomous Region with No.NJZY21153, Ordos Science and technology planning project with No.2021YYI18-46, Higher Education Reform Project of Ordos Applied College with No.KYYB2019007.
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The authors have no relevant financial or non-financial interests to disclose. Jin Li provided the algorithm and experimental results, wrote the manuscript, Tao Jin revised the paper, supervised and analyzed the experiment. We also declare that data availability and ethics approval is not applicable in this paper.
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Li, J., Jin, T. Intelligent real-time news communication platform in education. Mobile Netw Appl 27, 1218–1227 (2022). https://doi.org/10.1007/s11036-022-01948-0
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DOI: https://doi.org/10.1007/s11036-022-01948-0