Fake Job Recruitment Detection Using Machine Learning Approach
|International Journal of Engineering Trends and Technology (IJETT)||
|© 2020 by IJETT Journal|
|Year of Publication : 2020|
|Authors : Shawni Dutta, Prof.Samir Kumar Bandyopadhyay
|DOI : 10.14445/22315381/IJETT-V68I4P209S|
MLA Style: Shawni Dutta, Prof.Samir Kumar Bandyopadhyay "Fake Job Recruitment Detection Using Machine Learning Approach" International Journal of Engineering Trends and Technology 68.4(2020):48-53.
APA Style:Shawni Dutta, Prof.Samir Kumar Bandyopadhyay. Fake Job Recruitment Detection Using Machine Learning Approach International Journal of Engineering Trends and Technology, 68(4),48-53.
To avoid fraudulent post for job in the internet, an automated tool using machine learning based classification techniques is proposed in the paper. 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. Two major types of classifiers, such as single classifier and 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 single classifiers.
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Fake Job, Online Recruitment, Machine Learning, Ensemble Approach