Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/1041
Title: Career Aura–Smart Resume and Employment Recommender
Authors: Dissanayake, K
Mendis, S
Subasinghe, R
Geethanjana, D
Lunugalage, D
Kasthurirathna, D
Keywords: Career Aura – Smart
Smart Resume
Employment Recommender
Issue Date: 9-Dec-2021
Publisher: IEEE
Citation: K. Dissanayake, S. Mendis, R. Subasinghe, D. Geethanjana, D. Lunugalage and D. Kasthurirathna, "Career Aura – Smart Resume and Employment Recommender," 2021 3rd International Conference on Advancements in Computing (ICAC), 2021, pp. 353-358, doi: 10.1109/ICAC54203.2021.9671212.
Series/Report no.: 2021 3rd International Conference on Advancements in Computing (ICAC);Pages 353-358
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.
URI: http://rda.sliit.lk/handle/123456789/1041
ISBN: 978-1-6654-0862-2
Appears in Collections:Research Papers - Dept of Computer Science and Software Engineering
Research Papers - SLIIT Staff Publications

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