Open AccessFake E Job Posting Prediction Based on Advance Machine Learning Approachs
Author(s) -
Ali Raza,
Saqib Ubaid,
Faizan Younas,
Farhan Akhtar
Publication year - 2022
Publication title -
international journal of research publication and reviews
Language(s) - English
Resource type - Journals
ISSN - 2582-7421
DOI - 10.55248/gengpi.2022.3.2.7
Subject(s) - the internet , computer science , categorization , job analysis , selection (genetic algorithm) , internet users , text categorization , world wide web , artificial intelligence , machine learning , internet privacy , psychology , social psychology , job satisfaction
There are many jobs adverts on the internet, even on reputable job posting sites, that never appear to be false. However, following the selection, the so-called recruiters begin to seek money and bank information. Many candidates fall into their traps and lose a lot of money as well as their existing job. As a result, it is preferable to determine whether a job posting submitted on the site is genuine or fraudulent. Manually identifying it is extremely difficult, if not impossible! An automated online tool (website) based on machine learning-based categorization and algorithms are presented to eliminate fraudulent job postings on the internet. It aids in the detection of bogus job postings among the vast number of postings on the internet.