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Research on the Development Model of University Archives Cultural Products Based on Deep Learning

Qiong Luo*

School of Information Management, Nanjing University, Nanjing, 210023, China

* Corresponding Author: Qiong Luo. Email: email

Computer Systems Science and Engineering 2023, 46(3), 3141-3158. https://doi.org/10.32604/csse.2023.038017

Abstract

The products of an archival culture in colleges and universities are the final result of the development of archival cultural resources, and the development of archival cultural effects in colleges and universities should be an important part of improving the artistic level of libraries. The existing RippleNet model doesn’t consider the influence of key nodes on recommendation results, and the recommendation accuracy is not high. Therefore, based on the RippleNet model, this paper introduces the influence of complex network nodes into the model and puts forward the Cn RippleNet model. The performance of the model is verified by experiments, which provide a theoretical basis for the promotion and recommendation of its cultural products of universarchives, solve the problem that RippleNet doesn’t consider the influence of key nodes on recommendation results, and improve the recommendation accuracy. This paper also combs the development course of archival cultural products in detail. Finally, based on the Cn-RippleNet model, the cultural effect of university archives is recommended and popularized.

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APA Style
Luo, Q. (2023). Research on the development model of university archives cultural products based on deep learning. Computer Systems Science and Engineering, 46(3), 3141-3158. https://doi.org/10.32604/csse.2023.038017
Vancouver Style
Luo Q. Research on the development model of university archives cultural products based on deep learning. Comput Syst Sci Eng. 2023;46(3):3141-3158 https://doi.org/10.32604/csse.2023.038017
IEEE Style
Q. Luo, "Research on the Development Model of University Archives Cultural Products Based on Deep Learning," Comput. Syst. Sci. Eng., vol. 46, no. 3, pp. 3141-3158. 2023. https://doi.org/10.32604/csse.2023.038017



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