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<p>Based on artificial intelligence technology, this paper builds an innovation and entrepreneurship education platform for college students with the goal of improving their innovation and entrepreneurship spirit and ability. For faculty information, competition information, and other aspects related to the collection and analysis of student portraits. The use of a collaborative filtering algorithm allows students to receive personalized test questions while also modeling innovation and entrepreneurship competitions and creating a set of team-matching methods that utilize student portraits. Using hierarchical analysis to construct the evaluation system model of graduate innovation and entrepreneurship education, it can be analyzed that in the student portrait, when the students basically have no attendance, the assessment grade is also 0. Students who have participated in the innovation and entrepreneurship education platform have received salaries of more than 11K in 4 cities, while social workers have only received salaries of more than 11K in 1 city. Basically, more than 70% of those who agree with the learning mode of innovation and entrepreneurship platform and who are very interested in it are more than 70%. Resource allocation (0.3537) has the greatest influence on the cultivation of innovative and entrepreneurial talents, and the importance of constructing innovative and entrepreneurial resource allocation should be highly emphasized.</p>
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Based on artificial intelligence technology, this paper builds an innovation and entrepreneurship education platform for college students with the goal of improving their innovation and entrepreneurship spirit and ability. For faculty information, competition information, and other aspects related to the collection and analysis of student portraits. The use of a collaborative filtering algorithm allows students to receive personalized test questions while also modeling innovation and entrepreneurship competitions and creating a set of team-matching methods that utilize student portraits. Using hierarchical analysis to construct the evaluation system model of graduate innovation and entrepreneurship education, it can be analyzed that in the student portrait, when the students basically have no attendance, the assessment grade is also 0. Students who have participated in the innovation and entrepreneurship education platform have received salaries of more than 11K in 4 cities, while social workers have only received salaries of more than 11K in 1 city. Basically, more than 70% of those who agree with the learning mode of innovation and entrepreneurship platform and who are very interested in it are more than 70%. Resource allocation (0.3537) has the greatest influence on the cultivation of innovative and entrepreneurial talents, and the importance of constructing innovative and entrepreneurial resource allocation should be highly emphasized.

Research on Innovation and Entrepreneurship and Talent Cultivation Mode of College Students under the Background of Artificial Intelligence Technology

Applied Mathematics and Nonlinear Sciences

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

Based on artificial intelligence technology, this paper builds an innovation and entrepreneurship education platform for college students with the goal of...

Research on Innovation and Entrepreneurship and Talent Cultivation Mode of College Students under the Background of Artificial Intelligence Technology

Publié en ligne: 05 août 2024

Pages: -

Reçu: 23 avr. 2024

Accepté: 09 juil. 2024

DOI: https://doi.org/10.2478/amns-2024-2120

Mots clés
Collaborative filtering algorithm, Hierarchical analysis, Student portrait, Innovation and entrepreneurship education platform

© 2024 Hong Qian, published by Sciendo

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

Research on Innovation and Entrepreneurship and Talent Cultivation Mode of College Students under the Background of Artificial Intelligence Technology

Publié en ligne: 05 août 2024

Pages: -

Reçu: 23 avr. 2024

Accepté: 09 juil. 2024

DOI: https://doi.org/10.2478/amns-2024-2120

Mots clésCollaborative filtering algorithm, Hierarchical analysis, Student portrait, Innovation and entrepreneurship education platform

© 2024 Hong Qian, published by Sciendo

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

Mots clés
Collaborative filtering algorithm, Hierarchical analysis, Student portrait, Innovation and entrepreneurship education platform