Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/982
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dc.contributor.authorDissanayake, K.-
dc.contributor.authorMendis, S.-
dc.contributor.authorSubasinghe, R.-
dc.contributor.authorGeethanjana, D.-
dc.contributor.authorKasthurirathna, D.-
dc.date.accessioned2022-02-07T08:13:05Z-
dc.date.available2022-02-07T08:13:05Z-
dc.date.issued2021-12-09-
dc.identifier.issn978-1-6654-0862-2/21-
dc.identifier.urihttp://rda.sliit.lk/handle/123456789/982-
dc.description.abstractRecruitment 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.en_US
dc.description.sponsorshipCo-Sponsor:Institute of Electrical and Electronic Engineers (IEEE) Academic sponsor:SLIIT UNI Gold Sponsor :London Stock Exchange Group (LSEG)en_US
dc.language.isoenen_US
dc.publisher2021 3rd International Conference on Advancements in Computing (ICAC), SLIITen_US
dc.subjectNERen_US
dc.subjectLRen_US
dc.subjectRTen_US
dc.subjectDeep Learningen_US
dc.titleCareer Aura – Smart Resume and Employment Recommenderen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/ICAC54203.2021.9671212en_US
Appears in Collections:3rd International Conference on Advancements in Computing (ICAC) | 2021
Department of Computer Systems Engineering-Scopes
Research Papers - Dept of Computer Science and Software Engineering
Research Papers - IEEE
Research Papers - IEEE

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