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Title: An Intelligent Decision Support System For Recruitment: Resumes Screening and Applicants Ranking
Authors: Amro, Belal
Najjar, Arwa
Macido, Mario
Keywords: recruitment
Decision Support System (DSS),
intelligent Decision Support System (IDSS),
artificial intelligence AI
machine learning ML
Natural language processing NLP
Issue Date: 1-Jan-2022
Publisher: Slovensko društvo INFORMATIKA
Citation: Najjar, A., Amro, B., & Macedo, M. (2021). An Intelligent Decision Support System For Recruitment: Resumes Screening And Applicants Ranking. Informatica, 45(4).
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 machine learning and natural language processing techniques. I-Recruiter is composed of three sequentially connected blocks namely 1) Training block: which is responsible for training the model from a set of resumes, 2) Matching block: that is responsible for matching the resumes to the corresponding job description, and 3) Extracting block: that is responsible for extracting the top n ranked candidates. Experimental results for accuracy and performance showed that I-recruiter is capable of doing the job with high confidence and excellent performance.
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