<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Based on digital media technology, this paper defines Chinese art theory and, at the same time, combines digital media technology and the characteristics of Chinese art aesthetic discourse to construct an art aesthetic discourse system that covers the stage of sensory experience and the stage of “emotional experience”. In order to promote the digitalization of the art aesthetic discourse system, the MCFF algorithm is used to extract the features of art aesthetic discourse, match the features, and then merge the features of art aesthetic discourse based on the weighted summing algorithm so as to achieve the digitization of art aesthetic discourse features. The art aesthetic discourse system in digital media is analyzed based on the research data. The results show that compared with the traditional algorithm, the algorithm of this paper is better than the traditional algorithm in three aspects: pre-emphasis (growth rate of 62.70%), frame-plus-window (growth rate of 68.71%), and data conversion (growth rate of 72.14%). In addition, the aesthetic experiences of landscape painting and figure painting were 96.49±8.4 and 108.00±9.35 points, respectively, and F(1, 20)=20.746, p&lt;0.05, indicating that there is a significant difference in the sensory experience in the aesthetic discourse of art. This study can not only promote dialogue between art creators and scholars but also provide theoretical guidance and practical feedback for the future development of the art field.</p>
</abstract>

Based on digital media technology, this paper defines Chinese art theory and, at the same time, combines digital media technology and the characteristics of Chinese art aesthetic discourse to construct an art aesthetic discourse system that covers the stage of sensory experience and the stage of “emotional experience”. In order to promote the digitalization of the art aesthetic discourse system, the MCFF algorithm is used to extract the features of art aesthetic discourse, match the features, and then merge the features of art aesthetic discourse based on the weighted summing algorithm so as to achieve the digitization of art aesthetic discourse features. The art aesthetic discourse system in digital media is analyzed based on the research data. The results show that compared with the traditional algorithm, the algorithm of this paper is better than the traditional algorithm in three aspects: pre-emphasis (growth rate of 62.70%), frame-plus-window (growth rate of 68.71%), and data conversion (growth rate of 72.14%). In addition, the aesthetic experiences of landscape painting and figure painting were 96.49±8.4 and 108.00±9.35 points, respectively, and F(1, 20)=20.746, p<0.05, indicating that there is a significant difference in the sensory experience in the aesthetic discourse of art. This study can not only promote dialogue between art creators and scholars but also provide theoretical guidance and practical feedback for the future development of the art field.

The Use of Digital Media in the Construction of Chinese Art Theory and Art Aesthetic Discourse System

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

Based on digital media technology, this paper defines Chinese art theory and, at the same time, combines digital media technology and the characteristics of...

The Use of Digital Media in the Construction of Chinese Art Theory and Art Aesthetic Discourse System

Publié en ligne: 05 août 2024

Pages: -

Reçu: 29 mars 2024

Accepté: 22 juin 2024

DOI: https://doi.org/10.2478/amns-2024-2062

Mots clés
MCFF, Weighted summation algorithm, Feature fusion, Aesthetic discourse system

© 2024 Junfeng Ma, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

The Use of Digital Media in the Construction of Chinese Art Theory and Art Aesthetic Discourse System

Publié en ligne: 05 août 2024

Pages: -

Reçu: 29 mars 2024

Accepté: 22 juin 2024

DOI: https://doi.org/10.2478/amns-2024-2062

Mots clésMCFF, Weighted summation algorithm, Feature fusion, Aesthetic discourse system

© 2024 Junfeng Ma, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Mots clés
MCFF, Weighted summation algorithm, Feature fusion, Aesthetic discourse system