Employee Portrait Construction based on Deep Neural Networks

Abstract

Human management is critical in the enterprise. Employee portrait is a skill and method in modern human resource management and risk assignment. This paper proposes employee portraits based on a deep neural network. The employee portraits are abstracted from the labeling employee information model, such as employees' theoretical level, operational ability, exception handling level, accident analysis level, standard compliance level, and historical project level. Employee portraits can bring a particularly positive effect to the enterprise, improve the efficiency of human management, and help the enterprise's employees find more practical tasks, thereby improving the efficiency of the enterprise. In addition, we have also carried out a visual design for employee portraits so that enterprise managers can directly understand the status of employees. Finally, we demonstrate the effectiveness of the method.