An application of artificial intelligence based staff selection system

The most significant asset for an institution or business is its manpower. For the manpower to be strong, the right staff should be hired first. Today, staff requirements, candidate qualifications and the number of job applications have increased. This situation made the process of identifiying the right candidate more complex and difficult by increasing the amount of data to be analyzed to very high dimensions. The recruitment decision is a critical decision which is hard to reverse and has long-term consequences. This critical decision has to be made by a limited number of staff who have to follow many different tasks at the same time. Artificial intelligence is the primary technology that can help new staff selection, thanks to its ability to provide meaningful outputs by examining large-scale data. Within the scope of this thesis, in order to reduce the problems in recruitment process and to reach the right candidate in a shorter time, an application which can pre-eliminate by evaluating application forms with machine learning algorithms has been developed. With the application, recruitment teams will be able to perform the evaluation processes which can normally take days or weeks in a short time. It has been observed that machine learning algorithms trained with the evaluations made in the past can make predictions with high accuracy on new job applications.