Abstract:
As we are working to produce a deep learning model which will be using recurrent
neural network as it is best when we are using series ofdata which will help us identify
that whether a job ad is real or fraudulent We will be working to produce it with so
much efficiency with a hope that it will help big job portal websites to classify
ease that whether a job ad posted on their website is a fraud
This project is basically our final year project which we have chosen in order to
produce something helpful for our society as it will be extremely helpful if it is
produced correctly it will help people as the job requirement for companies
increasing day by day and companies are using big websites to drag good employers
to there companies so with the help ofthis classifier employers will detect that whether
with
or is legitimate.
are
a job ad posted on a website is either fraud or legitimate. The motivation for
choose to work on this project was that as there is a lot increase in unemployment and
the candidates are usingjob ads posted on websites to find a suitable job for themselves
and there is no way for them to find out whether a job ad posted on these websites is
legitimate or not so this model will help them get a better information about a job ad
that is it a fraud or a legitjob requirement.
us to
i
Fake job classification and detection can be done with great accuracy and precision.
As a result, in order to improve accuracy, machine learning and deep learning
algorithms must be applied to cleaned and pre-processed data. Further, deep learning
neural networks are used so as to achieve higher accuracy. Finally, all of these
classification models are compared to one another in order to determine which
classification algorithm has the best accuracy and precision.
