Automation of decision making process for selection of talented manpower considering risk factor: A data mining approach
Mohammed Mahmood Ali, Lakshmi Rajamani · 2012
Human Resource department (HR) plays vital and tedious role in recruiting manpower for organization and forced to use more accurate talent evaluation applications for selecting multi-talented personnel based on resumes, received in huge quantity but most of the talent evaluation applications are based on evaluating talent but not risk factors. This paper presents the solution for selecting appropriate talented personnel resumes without risk factors using association rule mining (ARM) technique of data mining. The automated intelligent agent based system (AIAS) built using knowledge-based system for decision making process on logical rules and facts obtained from domain expert and past learning experiences using ARM technique which guides the HR Department. The practical experimental results obtained from AIAS encourage HR department to take prompt decisions for recruiting talented personnel accurately without wasting interviewers time of employer and employee. The proposed system also reduces frequent resignations, improves performance of talented personnel without training cost and continuous monitoring.