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

<p>In this paper, cluster analysis is used to obtain the similarity coefficients as well as measurement scales among marketing characteristic variables in order to find the degree of stickiness of corporate marketing accurately. In order to avoid the over-fitting problem in the process of marketing research based on cluster analysis, it is necessary to optimize the attribute dependence through a rough set base and further explore the application of cluster analysis in marketing research. In the research design of marketing professional talent cultivation by integrating intelligent data analysis, the cleaning of research data can avoid the problem of initial data null value as well as duplication, and the evaluation database and data mining process are explained in the research. According to the marketing professional talent cultivation standards, to determine the research evaluation indexes, and to research and analyze the marketing professional talent cultivation path under the integration of industry and education. The results show that the regression coefficient of teaching form and student satisfaction of marketing teaching is 0.302, and the significance level Sig value is 0.000 (&lt;0.01). That is, the teaching form has a significant positive influence on the satisfaction of marketing majors individually. This study enhances the ability to integrate industry and education in vocational colleges and universities, driving the local economy and realizing a win-win situation between schools and enterprises.</p>
</abstract>

In this paper, cluster analysis is used to obtain the similarity coefficients as well as measurement scales among marketing characteristic variables in order to find the degree of stickiness of corporate marketing accurately. In order to avoid the over-fitting problem in the process of marketing research based on cluster analysis, it is necessary to optimize the attribute dependence through a rough set base and further explore the application of cluster analysis in marketing research. In the research design of marketing professional talent cultivation by integrating intelligent data analysis, the cleaning of research data can avoid the problem of initial data null value as well as duplication, and the evaluation database and data mining process are explained in the research. According to the marketing professional talent cultivation standards, to determine the research evaluation indexes, and to research and analyze the marketing professional talent cultivation path under the integration of industry and education. The results show that the regression coefficient of teaching form and student satisfaction of marketing teaching is 0.302, and the significance level Sig value is 0.000 (<0.01). That is, the teaching form has a significant positive influence on the satisfaction of marketing majors individually. This study enhances the ability to integrate industry and education in vocational colleges and universities, driving the local economy and realizing a win-win situation between schools and enterprises.

Research on Talent Cultivation Path for Marketing Majors under the Integration of Industry and Education Based on Intelligent Data Analysis

Applied Mathematics and Nonlinear Sciences

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

In this paper, cluster analysis is used to obtain the similarity coefficients as well as measurement scales among marketing characteristic variables in order...

Research on Talent Cultivation Path for Marketing Majors under the Integration of Industry and Education Based on Intelligent Data Analysis

Publié en ligne: 13 déc. 2023

Pages: -

Reçu: 15 févr. 2023

Accepté: 23 juin 2023

DOI: https://doi.org/10.2478/amns.2023.2.01475

Mots clés
Cluster analysis, Similarity coefficients, Measurement scales, Rough sets, Marketing

© 2023 Yang Wang, published by Sciendo

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

Research on Talent Cultivation Path for Marketing Majors under the Integration of Industry and Education Based on Intelligent Data Analysis

Publié en ligne: 13 déc. 2023

Pages: -

Reçu: 15 févr. 2023

Accepté: 23 juin 2023

DOI: https://doi.org/10.2478/amns.2023.2.01475

Mots clésCluster analysis, Similarity coefficients, Measurement scales, Rough sets, Marketing

© 2023 Yang Wang, published by Sciendo

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

Mots clés
Cluster analysis, Similarity coefficients, Measurement scales, Rough sets, Marketing