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

<p>This paper first analyzes the pain points and needs of voluntary college student volunteering in conjunction with college volunteering program management. Combined with the logic of generating a sense of acquisition for college students’ volunteer service, it explores the types of motivation that drive their volunteer demand. Based on deep learning, we propose volunteer integrity neural network prediction, classify volunteer integrity, and select different data sources to compare the running time and effectiveness of four classification algorithms, namely artificial neural network, Bayesian network, decision tree and support vector machine. Volunteer portraits are established with two dimensions: natural attributes and interest attributes. Deep feature extraction is utilized to recommend college volunteer activities. Among the sources of volunteering accessibility, 72.2% of college students consider volunteering information sources to be highly important. It can be seen that college volunteer service can help strengthen the construction of volunteer service information channels.</p>
</abstract>

This paper first analyzes the pain points and needs of voluntary college student volunteering in conjunction with college volunteering program management. Combined with the logic of generating a sense of acquisition for college students’ volunteer service, it explores the types of motivation that drive their volunteer demand. Based on deep learning, we propose volunteer integrity neural network prediction, classify volunteer integrity, and select different data sources to compare the running time and effectiveness of four classification algorithms, namely artificial neural network, Bayesian network, decision tree and support vector machine. Volunteer portraits are established with two dimensions: natural attributes and interest attributes. Deep feature extraction is utilized to recommend college volunteer activities. Among the sources of volunteering accessibility, 72.2% of college students consider volunteering information sources to be highly important. It can be seen that college volunteer service can help strengthen the construction of volunteer service information channels.

Exploring the Sustainable Development Path of College Volunteerism with Voluntarism in the Context of Deep Learning

SCHOOL OF POLITICAL SCIENCE AND LAW UNIVERSITY OF JINAN

People’s Public Security University of China

Applied Mathematics and Nonlinear Sciences

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

This paper first analyzes the pain points and needs of voluntary college student volunteering in conjunction with college volunteering program management....

Exploring the Sustainable Development Path of College Volunteerism with Voluntarism in the Context of Deep Learning

Data publikacji: 16 gru 2023

Zakres stron: -

Otrzymano: 24 sty 2023

Przyjęty: 26 cze 2023

DOI: https://doi.org/10.2478/amns.2023.2.01484

Słowa kluczowe
Neural network prediction, Deep learning, Deep feature extraction, Volunteer activity recommendation, College volunteer service

© 2023 Yumei Cao et al., published by Sciendo

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

Exploring the Sustainable Development Path of College Volunteerism with Voluntarism in the Context of Deep Learning

Data publikacji: 16 gru 2023

Zakres stron: -

Otrzymano: 24 sty 2023

Przyjęty: 26 cze 2023

DOI: https://doi.org/10.2478/amns.2023.2.01484

Słowa kluczoweNeural network prediction, Deep learning, Deep feature extraction, Volunteer activity recommendation, College volunteer service

© 2023 Yumei Cao et al., published by Sciendo

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

Słowa kluczowe
Neural network prediction, Deep learning, Deep feature extraction, Volunteer activity recommendation, College volunteer service