Online Recruitment Fraud Detection using ANN

Abstract

Online recruitment provides job-seekers an efficient search and reach for jobs. It also helps recruiters searching for qualified candidates which improves the recruitment process. However, employment scam has emerged as a critical issue. Some job posts are legitimate, and others are fraud. In this paper, an Artificial Neural Network based model is proposed to detect fraud job posts. The public Employment Scam Aegean Dataset (EMSCAD) is used with proper text preprocessing techniques for training and testing the proposed model. Our model has precision, recall, and f-measure of 91.84%, 96.02%, and 93.88% respectively. The results show that the proposed ANN-based model outperforms similar existing models in detecting fraud jobs.