A Study on the Job-Person Matching Model for Counselor Positions in Private Universities Based on the BP Neural Network

Abstract

With the popularization of higher education, the demand for counselor positions in private universities has been growing steadily. However, current job-person matching products on the market struggle to meet the actual needs of this position. This study focuses on counselor positions in private universities and constructs a job-person matching model based on the BP neural network algorithm, aiming to improve the accuracy and efficiency of counselor recruitment. By collecting and analyzing counselor competency feature data, the BP neural network model was trained and tested, verifying its feasibility and effectiveness. This study provides a scientific basis for counselor recruitment in private universities, helping to optimize the structure of the counselor team and enhance the work efficiency of counselors.