FAKE JOB RECRUITMENT DETECTION USING MACHINE LEARNING

Abstract

It is proposed in this research that a computerised apparatus that makes use of artificial intelligence-based organising strategies in order to avoid deceptive job postings on the internet be developed. Various classifiers are used to check for misleading information on the internet, and the findings of those classifiers are analysed in order to develop the most effective business trick detection model that can be used in the field of information security. When searching for fake job advertisements amid a large number of legitimate job ads, this tool may be really helpful. Solitary classifiers and troupe classifiers, to name a few examples, are two important types of classifiers that are used in the process of spotting bogus job postings on the internet. In any event, the results of the trials demonstrate that aggregating classifiers outperform solo classifiers when it comes to detecting tricks in general.