Data Mining for Prediction of Human Performance Capability in the Software Industry

• Published in: International journal of data mining & knowledge management process Vol. 5; no. 2; pp. 53 - 64
• Main Authors: Thakur, Gaurav Singh, Gupta, Anubhav, Gupta, Sangita
• Format: Journal Article
• Language: English
• Published: 31.03.2015
• Subjects: Bridges (structures); Colleges; Correlation; Criteria; Data mining; Human performance; Knowledge management; Personnel selection; Students
• ISSN: 2231-007X; 2230-9608
• DOI: 10.5121/ijdkp.2015.5205

In this paper, the authors aim to develop a framework that would allow any project manager to take the right decision for selecting new talent by correlating performance parameters with the other domain-specific attributes of the candidates. Also, another important motivation behind this project is to check the validity of the selection procedure often followed by various big companies in both public and private sectors which focus only on academic scores, GPA/grades of students from colleges and other academic backgrounds. Data-mining techniques provide useful information from the historical projects depending on which the hiring-manager can make decisions for recruiting high-quality workforce. This study aims to bridge this hiatus by developing a data-mining framework based on an ensemble-learning technique to refocus on the criteria for personnel selection. The results from this research clearly demonstrated that there is a need to refocus on the selection-criteria for quality objectives.