Intelligent Design and Implementation of Talent Cultivation Models Related to Employment Innovation and Entrepreneurship in Big Data Environment

Employment entrepreneurs in the big data environment need to learn continuously and update their knowledge and skills in order to better adapt to the market environment. This paper applies big data technology to reform the talent training mode related to employment innovation and entrepreneurship. First, the knowledge of employment innovation and entrepreneurship resources on the Internet is extracted, and a semantic matching matrix is established based on knowledge mapping. Secondly, the ternary vector and feature matrix are calculated to obtain the corresponding semantic matching matrix. Finally, the interest model (KG-NCF) is constructed and the personalized recommendation parameters are set to achieve personalized recommendations for employment innovation and entrepreneurship resources. In this paper, when the user’s browsing time reaches 6 seconds, the fitness between the recommended resources and the resources demanded by the user begins to converge to 100%. The difference between the resources recommended based on the knowledge graph and the user’s needs ranges from 1.41 to 2.91. It shows that the method of this paper can provide employment innovation and entrepreneurship education resources with a high degree of fit with users. Satisfaction survey of users using the method, the number of users agreeing with the effect of using employment innovation and entrepreneurship resources, the effect of resource recommendation, and the effect of comprehensively using the tool are in the majority. The use of this paper’s method has a profound effect on users’ communication, team awareness, and learning ability.