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Research on Wuhan's business environment based on intelligent business information data minning

Published: 27 January 2023 Publication History

Abstract

In order to optimize Wuhan's business environment and promote Wuhan's urban construction under the general trend of artificial intelligence development. This paper uses crawler technology to capture the 2020 intelligent business data of Wuhan, Hangzhou, Guangzhou and Zhengzhou. On the basis of the World Bank's business environment indicator system, we will determine the cost-benefit approach and build Wuhan's business environment indicator system. According to the principal component analysis, Wuhan ranked third among the four cities in terms of business environment. It is suggested to optimize Wuhan's business environment through a series of measures. Such as enhancing the integrity and sustainability of supporting policy systems. Creating a friendly, clean and integrated government environment and promote business facilitation. Reducing institutional transaction costs and ease the difficulty and high cost of financing for enterprises. Building an efficient innovation system and create a complete and high-quality environment. Creating a mutually beneficial, win-win opening up environment and enhance the internationalization level of cities.

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ICIIP '22: Proceedings of the 7th International Conference on Intelligent Information Processing
September 2022
367 pages
ISBN:9781450396714
DOI:10.1145/3570236
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 January 2023

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Author Tags

  1. Intelligent business information data
  2. business environment
  3. intercity data comparison

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ICIIP '22

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Overall Acceptance Rate 87 of 367 submissions, 24%

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