Abstract
Export trade, also known as export trade, refers to the trading activities of selling domestic products or processed products to overseas markets. Due to the large amount of export trade information and the limited storage of resources, the utilization rate of resources is low and the ability of information sharing is poor. To this end, this paper proposes a method of export trade information sharing based on social network data. Through the distributed classification technology of the blockchain platform, we can access trade financing data and information in real time and establish an information service mode. Bayesian estimation is used for data fusion. Establish social network data communication links to transmit information resources. Federal learning algorithm is used to map the original data into the corresponding data sharing model to realize the sharing of export trade information. The test results show that the export trade information sharing method based on social network data can improve the detection rate and shorten the running time, so as to maximize the utilization efficiency of shared information, and achieve better information sharing effect.
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References
Jiang, S., Deng, X., Zhou, X., et al.: Quantitative predictions of impacts of trade friction between China and the US on wheat trade and its embodied carbon emissions. J. Agro-Environ. Sci. 39(4), 762–773 (2020)
Yang, C.: Research of effect of experienced utility on continuous sharing intention of knowledge in social network. Mod. Inf. 40(3), 88–102, 110 (2020)
Ding, X.: Medical Image Information Interactive Sharing System Based on Local Weighted Fitting Algorithm. Techn. Autom. Appl. 14(7), 101–104 (2022)
Lin, H., Li, R.: Research on financial information sharing based on Improved SVM model. Mod. Sci. Instr. 39(3), 219–223 (2022)
Jia, P., Yin, C.: Research on characteristics and rules of information transmission in blockchain social network. Inf. Sci. 39(1), 35–40, 47 (2021)
Gao, A., Liang, Y., Xie, X., et al.: Social network information diffusion method with support of privacy protection. J. Front. Comput. Sci. Technol. 15(2), 233–248 (2021)
Fang, J., Qian, X.: Information dissemination of social network in improved scir information propagation model. Comput. Eng. Appl. 56(19), 105–113 (2020)
Shi, X.: Simulation of cloud-driven IoT information sharing security mechanism. Comput. Simul. 37(9), 140–144 (2020)
Liu, X.-Y., He, D.-B.: Research on of competitive nonlinear dynamic information diffusion modeling in online social network. Chin. J. Comput. 43(10), 1842–1861 (2020)
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© 2023 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Yang, G. (2023). Research on Export Trade Information Sharing Method Based on Social Network Data. In: Fu, W., Yun, L. (eds) Advanced Hybrid Information Processing. ADHIP 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 468. Springer, Cham. https://doi.org/10.1007/978-3-031-28787-9_38
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DOI: https://doi.org/10.1007/978-3-031-28787-9_38
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