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Intelligent analysis of e-government influence factors based on improved machine learning

  • S.I. : Machine Learning based semantic representation and analytics for multimedia application
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Abstract

In order to improve the effect of e-government work, it is necessary to analyze its influencing factors. E-government is affected by many social factors, so it is necessary to combine intelligent models to improve the effect of factor analysis. This paper combines the essence of e-government influencing factor data to improve the machine learning algorithm and uses the EM algorithm to derive the parameter estimation formula of the data in the case of missing data to improve the accuracy of data analysis. Moreover, this article combines the structure of the e-government system to build the main structure of the intelligent analysis model of the influence factors of e-government. According to the key influencing factor model of e-government adoption and multi-dimensional research on technology, organization and implementation, this paper puts forward the model and promotion mode of the e-government system based on cloud computing and conducts a simulation. From the simulation results, the effect of the model proposed in this paper is more significant.

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Authors and Affiliations

  1. Department of Electronic Business, South China University of Technology, Guangzhou, 510000, China

    Lili Wei

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  1. Lili Wei
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Correspondence to Lili Wei.

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Wei, L. Intelligent analysis of e-government influence factors based on improved machine learning. Neural Comput & Applic 34, 12241–12256 (2022). https://doi.org/10.1007/s00521-021-06657-5

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  • DOI: https://doi.org/10.1007/s00521-021-06657-5

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