An intelligent career planning matching system and method fusing elements of innovation and entrepreneurship

Abstract

The application provides an intelligent career planning matching system and method integrating innovation and entrepreneurship elements, applied to the technical field of data processing. The application collects personal career appeal, ability characteristics and other data, and innovation and entrepreneurship resources, industry trends and other external data, removes redundancy based on a feature screening algorithm, generates a standardized career-resource feature sequence, and then converts it into a supply-demand matching relationship network graph, processes it through a hybrid modeling tool, subdivides the scene through a hierarchical clustering algorithm, and constructs a dynamic supply-demand coupling model. Based on the model, a matching fitness function is set, an improved genetic algorithm is used to build an optimization equation, and a key matching gap value is calculated. Combined with the gap value, an index is proposed, grades are divided, and a multi-dimensional matching feature matrix is established. By comparing real-time and benchmark data, an optimization potential coefficient is generated. Combined with the coefficient and personal planning grouping path, key factors are screened to establish an adaptive matching optimization model, and finally real-time matching suggestions and career planning optimization schemes are output.

Images