Publication: Career Aura – Smart Resume and Employment Recommender
Type:
Article
Date
2021-12-09
Journal Title
Journal ISSN
Volume Title
Publisher
2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT
Abstract
Recruitment and Job seeking are two major
factors that are directly proportional to each other. Due
to the competitive nature of the present world, the process
of acquiring the best resource effectively and efficiently
has become a challenging aspect for the companies. As a
result, modern job portals have become increasingly
popular to address the challenges identified in the early
recruitment and job search process. The purpose of this
research is to introduce an optimal solution to address the
ineffective areas identified in the job and recruitment
domain which can further enhance the recruitment and
job seeking decisions by utilizing deep learning and
sentiment analytic approach along with descriptive
analysis. The proposed system recommends the relevant
job opportunities by omitting the irrelevant job
advertisements for job hunters who are interested in the
IT job domain while they input their resume to the system
and additionally, they can improve their career decisions
by adhering to the prediction schemes. Moreover, the
system facilitates recruiters to headhunt top talents
efficiently once they input job requirements to the system
and candidate suggestions are not only made depending
on their resume information but also analyzing their
LinkedIn endorsements.
Description
Keywords
NER, LR, RT, Deep Learning
