Multi-Dimensional Quantitative Model for Evaluating the Practicality of Enterprise Information Systems

This article aims to explore a more accurate and comprehensive assessment method of enterprise information system (EIS) practicality. In view of the shortcomings of the existing assessment methods, this article proposes a multidimensional quantitative model based on deep learning technology to achieve accurate assessment of the practicality of information systems. The experimental results show that the deep learning model proposed in this article is obviously superior to the traditional ID3 algorithm in recall and accuracy, with an increase of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{1 8. 7 5 \%}$</tex> and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{2 2. 1 7 \%}$</tex> respectively. This result proves the superiority of deep learning model in EIS practical assessment. To sum up, this study successfully constructed a multi-dimensional quantitative model of EIS practicality assessment based on deep learning technology, and realized the accurate assessment of information system practicality. The model improves the accuracy and comprehensiveness of assessment and provides more powerful data support for enterprise decision-making. The research results are of great significance for the optimization and upgrading of EIS, and also provide useful reference for the subsequent related research.