A COMPARATIVE STUDY OF FAKE JOB POST PREDICTION USING DIFFERENT DATA MINING TECHNIQUES

Abstract: The study suggests an automated way of preventing bogus job postings online that uses categorisation techniques based on machine learning. To determine the most effective model for identifying job scams, the output of multiple classifiers was compared. In order to verify false internet postings, these classifiers are used. In the midst of several other ads, it aids in identifying fraudulent job listings. The two fundamental categories of classifiers considered for the purpose.