Web-based System for Identifying Fraudulent Job Advertisements with Machine Learning

To prevent false job advertisements on the internet, the study proposes a robotized framework that employs machine learning-based classification techniques. Various classifiers are employed to approve fraudulent web posts, and the results are compared to find the most effective job trick location technique. It helps identify fake job advertisements among a big number of posts. For detecting fake job postings, two major classifier types are considered: single classifiers and outfit classifiers. Nonetheless, the test results show that ensemble classifiers outperform single classifiers in task recognition.