Abstract
In the era of Internet economy, cross-border e-commerce shopping guides were conducted under the conditions of virtual network environment. Therefore, the traditional cross-border e-commerce shopping guide system had long been unable to meet the diversified needs of cross-border e-commerce shopping guides. A cross-border e-commerce shopping guide system combining big data and AI technology was proposed and designed. Using big data and AI technology, the hardware and software of the cross-border e-commerce shopping guide system were analyzed respectively, and the optimized design of the cross-border e-commerce shopping guide system was completed. The experimental data showed that the cross-border e-commerce shopping guide system combining big data and AI technology had better performance than the traditional system, and could better meet the technical requirements of cross-border e-commerce shopping guide.
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Acknowledgements
“Innovation Research on Cross-border E-commerce Shopping Guide Platform Based on Big Data and AI Technology”, Funded by Ministry of Education Humanities and Social Sciences Research and Planning Fund (No.: 18YJAZH042); Key Research Platform Project of Guangdong Education Department (No.: 2017GWTSCX064); The 13th Five-Year Plan Project of Philosophy and Social Science Development in Guangzhou (No.: 2018GZGJ208).
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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Li, J. (2019). Optimization Design of Cross-Border E-commerce Shopping Guide System Combining Big Data and AI Technology. In: Gui, G., Yun, L. (eds) Advanced Hybrid Information Processing. ADHIP 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 301. Springer, Cham. https://doi.org/10.1007/978-3-030-36402-1_20
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DOI: https://doi.org/10.1007/978-3-030-36402-1_20
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