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

<p>This paper constructs a Bayesian network text recognition model based on the Bayesian network and explores the role of Chinese language literature in the dissemination of traditional culture by analyzing the embodiment of traditional culture in Chinese language literature network texts. The collection process of Chinese language and literature data in network text is analyzed from the perspective of textual data interaction. The information of node variables in a Bayesian network is used to determine the mutual relationship between Chinese language literature and traditional culture. The degree of interdependence between Chinese literature and traditional culture can be measured by combining mutual information. The results show that the correct rate of text recognition of the Bayesian text recognition model decreases slightly when the training samples are (100-300), but the correct rate always stays around 0.85, thus reflecting the effectiveness of the network recognition model in this paper. Chinese language literature has a certain role in the dissemination of traditional culture, which proves that Chinese language literature, as a carrier of traditional culture, can improve the dissemination speed of traditional culture. This study focuses on the integration of Chinese literature and traditional communication to improve a new vision.</p>
</abstract>

This paper constructs a Bayesian network text recognition model based on the Bayesian network and explores the role of Chinese language literature in the dissemination of traditional culture by analyzing the embodiment of traditional culture in Chinese language literature network texts. The collection process of Chinese language and literature data in network text is analyzed from the perspective of textual data interaction. The information of node variables in a Bayesian network is used to determine the mutual relationship between Chinese language literature and traditional culture. The degree of interdependence between Chinese literature and traditional culture can be measured by combining mutual information. The results show that the correct rate of text recognition of the Bayesian text recognition model decreases slightly when the training samples are (100-300), but the correct rate always stays around 0.85, thus reflecting the effectiveness of the network recognition model in this paper. Chinese language literature has a certain role in the dissemination of traditional culture, which proves that Chinese language literature, as a carrier of traditional culture, can improve the dissemination speed of traditional culture. This study focuses on the integration of Chinese literature and traditional communication to improve a new vision.

Exploring the Role of Chinese Language and Literature in the Transmission of Traditional Culture by Combining the Method of Internet Text Analysis

Henan University of Technology Luohe Institute of Technology

Applied Mathematics and Nonlinear Sciences

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

This paper constructs a Bayesian network text recognition model based on the Bayesian network and explores the role of Chinese language literature in the...

Exploring the Role of Chinese Language and Literature in the Transmission of Traditional Culture by Combining the Method of Internet Text Analysis

Online veröffentlicht: 05. Dez. 2023

Seitenbereich: -

Eingereicht: 15. März 2023

Akzeptiert: 15. Juni 2023

DOI: https://doi.org/10.2478/amns.2023.2.01374

Schlüsselwörter
Bayesian network, Network text analysis, Chinese language and literature, Data interaction, Traditional culture dissemination

© 2023 Bi Zhao, published by Sciendo

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

Exploring the Role of Chinese Language and Literature in the Transmission of Traditional Culture by Combining the Method of Internet Text Analysis

Online veröffentlicht: 05. Dez. 2023

Seitenbereich: -

Eingereicht: 15. März 2023

Akzeptiert: 15. Juni 2023

DOI: https://doi.org/10.2478/amns.2023.2.01374

SchlüsselwörterBayesian network, Network text analysis, Chinese language and literature, Data interaction, Traditional culture dissemination

© 2023 Bi Zhao, published by Sciendo

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

Schlüsselwörter
Bayesian network, Network text analysis, Chinese language and literature, Data interaction, Traditional culture dissemination