Data Mining Technology In Human Resource Management

Competitions among enterprises become more severe along with the escalating of the status of market economy. Competition in talents rises into the vital element of competitions among enterprises, which owns corresponding talents will occupy the market. In order to achieve the predominance in competition, an enterprise should escalate its value, take effective management measures, enhance the strategy in human resource management, and actually realize the goal of taking talents as its foundation.This dissertation is based on the management concept to magnitude data of human resource system modules such as recruitment, demission, performance, payroll and training. By analyzing these modules, enterprise could combine human resource management and data management. The dissertation introduces data mining concept and its six most common methodology as following, description and statistics, association and relation, classification, prediction, optimization, structure formula module.According to the property of human resource system with abundant raw data and hard to identify or predict, the dissertation introduces rough calculation and decision tree. By analyzing and implementing ID3 and SLIQ algorithm into human resource system module, the dissertation has provided reliable and stable support for human resource management to make scientific decisions.The purpose of this dissertation is to deepen people's recognition of combination of human resource management and data management, to enhance the understanding that human resource management will bring valuable profit. With more and more experts involving in this field, and giving birth to more and more matured data mining tools and algorithm, human resource management will embrace a bright future.