Prediction of Job Openings in IT Sector using Long Short -Term Memory Model

Addressing the unemployment problem is a bit challenging task. The non-engineering graduates can work in all the sectors, whereas engineering graduates can work in their designated job domain. So, the engineering graduate needs to be guided in getting the employment opportunity in their job domain. The unemployment rate in India is increasing drastically every year. The unemployment of engineering graduates is mainly due to the lack of knowledge on various job categories and all the graduates are enriching their skills in the attractive domain or the upcoming technologies. So, the graduates are falling only in a specified job category where the competition is more. This problem must be resolved by guiding the graduates. There is a need for a balanced approach in guiding the graduates to avoid the problem of searching for the job in the attractive domain. This paper presents a new method to predict the number of job openings based on location and job category using the Long Short-Term Memory model (LS TM). After the series of experiments conducted, the results show that the proposed method is 96% effective. The performance of the proposed system is found to be superior to the Simple Recurrent Neural Network (SRNN). By using the proposed model, the graduates are benefited in getting knowledge about the current job opportunities.