Smart Talents Recruiter - Resume Ranking and Recommendation System

During the previous decade, the augmentation of automatic e-recruitment has led to the enlargement of web channels that are devoted to candidate dissemination. In an economic and strategic context where cost-effective is basal, the recommendation of the candidates for the given job requirements has...

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Bibliographic Details
Published in2018 IEEE International Conference on Information and Automation for Sustainability (ICIAfS) pp. 1 - 5
Main Authors Mohamed, Ashif, Bagawathinathan, Wickram, Iqbal, Usama, Shamrath, Shahik, Jayakody, Anuradha
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2018
Subjects
Data mining
Information technology
NLP
Ontologies
Ontology
OWL
Portals
Qualifications
Recruitment
Resumes
SPARQL
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Summary:During the previous decade, the augmentation of automatic e-recruitment has led to the enlargement of web channels that are devoted to candidate dissemination. In an economic and strategic context where cost-effective is basal, the recommendation of the candidates for the given job requirements has become mandatory. The purpose of this work is to acquaint the actual results that we have achieved on a new recommendation system named Smart Applicant Ranker which is a candidate recommendation tool designed to supervise recruiters while they input their job requirements into the system. This system is designed using Ontology where we can compare the resume models with the given job requirements to match the best comparable candidates. Two ranking algorithms are underlined in this system which will be invoked to assign a ranking point to the recommended candidates against the other candidates on the recommendation pool. The Smart Applicant Ranker system will be kept in a Semantic Web approach that provides IT recruitment firms to seek experts in an efficient way.
ISSN:2151-1810
DOI:10.1109/ICIAFS.2018.8913392