Minh Thanh Vo1, Anh H. Vo2, Trang Nguyen3, Rohit Sharma4, Tuong Le2,5,*
CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 521-535, 2021, DOI:10.32604/cmc.2021.015645
Abstract In recent years, the detection of fake job descriptions has become increasingly necessary because social networking has changed the way people access burgeoning information in the internet age. Identifying fraud in job descriptions can help jobseekers to avoid many of the risks of job hunting. However, the problem of detecting fake job descriptions comes up against the problem of class imbalance when the number of genuine jobs exceeds the number of fake jobs. This causes a reduction in the predictability and performance of traditional machine learning models. We therefore present an efficient framework that uses an oversampling technique called FJD-OT… More >
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