2021
DOI: 10.31449/inf.v45i4.3356
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An Intelligent Decision Support System For Recruitment: Resumes Screening And Applicants Ranking

Abstract: The task of finding the best job candidates among a set of applicants is both time and resource-consuming, especially when there are lots of applications. In this concern, the development of a decision support system represents a promising solution to support recruiters and facilitate their job. In this paper, we present an intelligent decision support system named I-Recruiter, that ranks applicants according to the semantic similarity between their resumes and job descriptions; the ranking process is based on… Show more

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Cited by 12 publications
(8 citation statements)
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“…The study suggested many automated systems with different techniques. Najjar, Amro & Macedo (2021) studied an automated approach for intelligent applicant screening for hiring by using ontology mapping. In order to suggest the best resumes for job postings utilizing a similarity assessment, their research concentrated on developing ontology papers for candidates’ difficulties.…”
Section: Related Workmentioning
confidence: 99%
“…The study suggested many automated systems with different techniques. Najjar, Amro & Macedo (2021) studied an automated approach for intelligent applicant screening for hiring by using ontology mapping. In order to suggest the best resumes for job postings utilizing a similarity assessment, their research concentrated on developing ontology papers for candidates’ difficulties.…”
Section: Related Workmentioning
confidence: 99%
“…Currently, RPA is being utilized in the human resources industry to automate a range of tasks, such as recruiting new employees, handling payroll, and administering benefits [38]. By automating repetitive operations that have historically been done by people, RPA has the potential to decrease errors and boost efficiency [39].…”
Section: Human Resourcesmentioning
confidence: 99%
“…A well-designed framework can unlock the value of both data and algorithms, effectively integrating the closed-loop decision-making process, enabling continuous learning of medical knowledge, and optimizing decision-making. It forms the foundation for constructing a reliable intelligent medical decision support system [10].See Figure 2 for the system framework.…”
Section: Overall Framework Designmentioning
confidence: 99%