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

<p>In this paper, firstly, we start from the imagery in the poem, excavate the resources of the ideology and politics in the university language poetry, and put forward the feasible path of the integration of the ideology and politics of the university language course and the poetry culture of the family training. The research on poetry culture in university language is conducted using a deep learning model. Based on the deep learning model, keywords in the poetry text are extracted and extended, taking into account the issue of word splitting and lexical annotation. The sequence coding of word vectors is needed so as to construct a poetry generation model based on RNNPG, and then the research and analysis on the concept of ideology and politics of the poetry culture in the university language are carried out. The results show that in terms of model performance, the RNNPG model is 1.17 overall, and the overall generation effect is more ideal compared to other single discriminator generation models. The acceptance level of sophomores is generally above 0.29, which is better than that of freshmen, and the teaching of ancient poems under the perspective of “curriculum politics” is especially necessary to improve their cultural taste and aesthetic interest. This study is conducive to the personalized development of students and the formation of correct concepts.</p>
</abstract>

In this paper, firstly, we start from the imagery in the poem, excavate the resources of the ideology and politics in the university language poetry, and put forward the feasible path of the integration of the ideology and politics of the university language course and the poetry culture of the family training. The research on poetry culture in university language is conducted using a deep learning model. Based on the deep learning model, keywords in the poetry text are extracted and extended, taking into account the issue of word splitting and lexical annotation. The sequence coding of word vectors is needed so as to construct a poetry generation model based on RNNPG, and then the research and analysis on the concept of ideology and politics of the poetry culture in the university language are carried out. The results show that in terms of model performance, the RNNPG model is 1.17 overall, and the overall generation effect is more ideal compared to other single discriminator generation models. The acceptance level of sophomores is generally above 0.29, which is better than that of freshmen, and the teaching of ancient poems under the perspective of “curriculum politics” is especially necessary to improve their cultural taste and aesthetic interest. This study is conducive to the personalized development of students and the formation of correct concepts.

Analyzing the Integration Interpretation of Civics and Family Poetry Culture in University Language Programs Based on Deep Learning Models

Applied Mathematics and Nonlinear Sciences

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

In this paper, firstly, we start from the imagery in the poem, excavate the resources of the ideology and politics in the university language poetry, and put...

Analyzing the Integration Interpretation of Civics and Family Poetry Culture in University Language Programs Based on Deep Learning Models

Online veröffentlicht: 13. Nov. 2023

Seitenbereich: -

Eingereicht: 14. Jan. 2023

Akzeptiert: 24. Mai 2023

DOI: https://doi.org/10.2478/amns.2023.2.01122

Schlüsselwörter
Deep learning, RNNPG, Poetry generation model, Word vectors, Sequence coding, Curriculum thinking

© 2023 Liping Cai, published by Sciendo

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

Analyzing the Integration Interpretation of Civics and Family Poetry Culture in University Language Programs Based on Deep Learning Models

Online veröffentlicht: 13. Nov. 2023

Seitenbereich: -

Eingereicht: 14. Jan. 2023

Akzeptiert: 24. Mai 2023

DOI: https://doi.org/10.2478/amns.2023.2.01122

SchlüsselwörterDeep learning, RNNPG, Poetry generation model, Word vectors, Sequence coding, Curriculum thinking

© 2023 Liping Cai, published by Sciendo

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

Schlüsselwörter
Deep learning, RNNPG, Poetry generation model, Word vectors, Sequence coding, Curriculum thinking