Potential Data Mining Classification Techniques for Academic Talent Forecasting

Abstract

Classification and prediction are among the major techniques in data mining and widely used in various fields. In this article we present a study on how some talent management problems can be solved using classification and prediction techniques in data mining. By using this approach, the talent performance can be predicted by using past experience knowledge discovered from the existing database. In the experimental phase, we have used selected classification and prediction techniques to propose the appropriate techniques from our training dataset. An example is used to demonstrate the feasibility of the suggested classification techniques using academician performance data. Thus, by using the experiments results, we suggest the potential classification techniques for academic talent forecasting.