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Optimization Design of Cross-Border E-commerce Shopping Guide System Combining Big Data and AI Technology

  • Jiahua LiEmail author
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 301)

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.

Keywords

Big data AI technology Cross-border E-commerce shopping guide system Optimized design 

Notes

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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Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2019

Authors and Affiliations

  1. 1.Guangzhou Vocational and Technical University of Science and TechnologyGuangzhouChina

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