Research on Intelligent Matching Model Between Employees and Positions Based on Python Big Data Analysis

Abstract

In order to improve the efficiency and accuracy of human resource management by big data technology, support vector machines are used to complete job matching. The element sample for the employee indicator is sparsely represented to obtain the matrix. The sample is binary classification by a support vector machine to judge the matching degree of employees to positions. Finally, the random transformation function is introduced to achieve dynamic recommendations in the big data environment. The experimental results show that the algorithm has high job matching accuracy, high dynamic recommendation efficiency, and batch recommendation.