Paper Contents
Abstract
In recent years, due to advancement in modern technology and social communication, advertising new job posts has become very common issue in the present world.So, fake job posting prediction task is going to be a great concern for all. Like many otherclassification tasks, fake job posing prediction leaves a lot of challenges to face. This paper proposed to use different data mining techniques and classification algorithm like LogisticRegression, support vector machine, naive bayes classifier, random forest classifier, to predict ajob post if it is real or fraudulent. Our application was built which takes Job Id, Description andjob Requirements to predict whether the given job post is real or fake. We have experimented on Employment Scam Aegean Dataset (EMSCAD) containing 18000 samples. The trained classifier shows approximately 98% classification accuracy to predicts fraudulent job post
Copyright
Copyright © 2023 R.GEYAMRUTHA. This is an open access article distributed under the Creative Commons Attribution License.
