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Academic Journal of Business & Management, 2019, 1(2); doi: 10.25236/AJBM.190116.

Analysis of “Belt and Road” Sino-Russian trade big data ecological environment based on web crawler

Author(s)

Lin Xia*

Corresponding Author:
Lin Xia
Affiliation(s)

Globalization and Global Issues Institute, China University of Political Science and Law, Beijing 100088, China
*Corresponding author: XIA Lin, e-mail: xialin666@126.com

Abstract

In order to promote the “Belt and Road” Sino-Russian friendly trade, the advanced web crawler technology is used for data analysis in the context of the rapid development of Internet of Things technology. The types and applications of web crawler in big data are described; then, the web crawler technology is applied to the big data ecological environment analysis of “Polar Silk Road” of “Belt and Road” Sino-Russian trade. The steps of applying web crawler to the big data ecological environment analysis of “Polar Silk Road” are explained first; next, the analysis results are clarified. The research results have shown that the Sino-Russian trade ecological environment analysis based on web crawler technology is more perfect, which promotes the application and propagation of web crawler technology. The analysis has pointed out that being the cooperation project of Sino-Russian “Belt and Road”, the “Polar Silk Road” is facing a huge test in terms of its ecological environment, in which the oil spills occurred in oil and gas transportation projects have become the most important source of pollution in the Arctic region. These ecological problems require China and Russia to strengthen the development and construction in the fields of marine biological development, navigation work, fishery market, natural energy, etc. to further promote the construction and development of the ecological environment of the “Polar Silk Road”.

Keywords

Big data; Web crawler; Technological application; Sino-Russian trade

Cite This Paper

Lin Xia. Analysis of “Belt and Road” Sino-Russian trade big data ecological environment based on web crawler. Academic Journal of Business & Management (2019) Vol. 1, Issue 2: 7-12. https://doi.org/10.25236/AJBM.190116.

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