Design and Implementation of Fake Job Post Detection using Machine Learning Techniques

Abstract

To avoid fraudulent post for job in the internet, it is a one of the machine learning technique based on classification techniques is proposed in the project. Different classifiers are used for checking fraudulent post in the web and the results of those classifiers are compared for identifying the best employment scam detection model. It helps in detecting fake job posts from an enormous number of posts. The major classifier, such as ensemble classifiers are considered for fraudulent job posts detection. However, experimental results indicate that ensemble classifiers are the best classification to detect scams over the other classifiers.