Research on the cultivation of innovative entrepreneurial talents for digital transformation of enterprises based on association rule algorithm

Jia Xu

International Journal of Knowledge-Based Development, 2023, vol. 13, issue 2/3/4, 113-130

Abstract: A talent development framework for enterprises is proposed to address the new requirements for talent development in the digital transformation stage. Through the study of the enterprise employee training framework, an employee data mining based on the improved Apriori association algorithm is proposed to realise the visual analysis of employee work performance. The experimental results show that the improved Apriori correlation algorithm takes 17s to process 7500 things, which is better than the traditional Apriori correlation algorithm. The performance score of employees is negatively correlated with the business volume of the enterprise. There is a problem of delay in the processing of complex work content by employees. And there is a positive correlation between the time and number of online learning and employee quality in talent development. The content of the study has important reference significance for the digital transformation of enterprises and the management of enterprise performance innovation.

Keywords: association rule algorithm; talent development framework; performance management; enterprise innovation development. (search for similar items in EconPapers)
Date: 2023
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