Optimization of Person-Post Matching Model for Improving Economic Management Ability

With the application of digital scenes of human resources, in order to improve the economic management ability of talents, it is necessary to establish scene rules according to the tag library and portraits of economic management talents, posts and tasks, and establish a matching model of people and posts. In order to improve the economic management ability, an optimized design method of a matching model of people and posts based on big data fusion is proposed. The application rules for the screened tags is designed based on the scenario requirements, we assign values and design weights for the tags in the calculation and scoring model in combination with economic management promotion and model optimization, the relevant business scenario tags is selected based on the economic management talent tags according to the business scenario requirements of cadre optimization and job matching, the application rules is designed, the tag weights is set by adopting the methods of big data fusion and sample tag identification, and the fuzzy feature rule detection and correlation analysis are taken. According to the business application suggestions, three types of quick screening rules are provided for employers to choose or customize other quick screening rules, so as to realize the optimal design of the economic manager's job matching model.