| Machinery manufacturing industry is a basic industry for China’s economic development,with a long history of development and the mission of providing the required equipment for national economic development.In the background of rapid development of globalization,all industries are facing new opportunities and challenges.In order to change the status of China’s manufacturing industry in the international arena and realize the transformation of China’s identity to a manufacturing power,the cultivation of applied talents in mechanical engineering has become very critical.The development of any industry is inseparable from the application of professional knowledge in the field of talent.Talent is an important factor affecting the direction of development of an industry.Mechanical manufacturing industry can be benign development and mechanical engineering application of talent training effect is closely related.In recent years,with the continuous improvement of science and technology level and the rapid development of the industry,the demand for applied talents is also higher and higher.In this situation,measures to improve the quality of engineering education in China need to be analyzed to provide research ideas on how to deliver more high-quality engineering applied talents for the economic development of China.In order to solve the above mentioned problems,the main work done in this paper is as follows:(1)According to the research needs of the study on the factors influencing the training of applied talents in mechanical engineering,the data needed for the study were collected and processed.The appropriate data features were selected and labeled for the next step of the study.(2)According to the data size and data characteristics of the dataset,the Apriori algorithm and FP-Growth algorithm were improved.Two algorithms were proposed:Apriorihst algorithm and FPMAX algorithm,which were used for the analysis of correlation between experimental data.(3)On the basis of the obtained algorithmic correlation analysis results,the experimental results were rearranged and labeled.The knowledge graph technology was used to construct a knowledge graph of the influencing factors for the cultivation of applied talents in mechanical engineering.The correlation between the influencing factors was visualized.On this basis,the correlations among the factors were analyzed in a targeted manner by querying operations on the knowledge graph of influencing factors.The credibility of the research findings was verified by comparing with the actual situation of the 2022 graduates.(4)Exploring the universality of the research method used in this study,using the vehicle engineering major as a research example,and analyzing the application and promotion of the proposed influence factor research method to other majors under the mechanical discipline.At the same time,the credibility of the research findings was verified.The results showed that the improved Apriorihst algorithm and FPMAX algorithm can provide a better analysis of the correlation between the factors influencing the cultivation of applied talents in mechanical engineering,and the constructed knowledge graph of the influencing factors can show the analysis results intuitively.The keyword query operation can be used for targeted analysis.The research results showed that factors such as stronger practical and theoretical abilities had a greater influence on the cultivation of applied talents in mechanical engineering.By comparing with the actual situation,the reliability of the research conclusion is verified.At the same time,the research method proposed in this paper had been applied well in vehicle engineering majors,and had certain promotion value in other majors under mechanical discipline.This can provide a basis for revision of cultivation plan and modification of education syllabus for cultivation plan revisers,and help professional decision makers to formulate and implement cultivation policies. |
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