Understanding Job Requirements Using Natural Language Processing

Keywords:
e-administration, public administration, administrative procedures.

Abstract:
With the rising number of remote jobs and mediums on which companies rely as funnels to attract job candidates, the number of job applications receives increases exponentially over time. Human Resource (HR) departments are becoming bottlenecks for pleasant applicant experiences because of the laboriousness of the application processing task. Increasing the size of HR departments works to a certain point but hiring more HR specialists becomes impossible from a financial and managerial standpoint. We propose a novel approach for candidate filtering based on competence matching between job ads created by companies and submitted resumes. The proposed system achieves 99.5% accuracy and relies on natural language processing techniques to extract information from both candidates' resumes and job ads. It allows companies to create their personalized automated filters using the extracted information.

CITATION:

IEEE format

Copy to clipboard

L. Aničin, M. Stojmenović, “Understanding Job Requirements Using Natural Language Processing,” in Sinteza 2022 - International Scientific Conference on Information Technology and Data Related Research, Belgrade, Singidunum University, Serbia, 2022, pp. 457-463. doi:10.15308/Sinteza-2022-457-463

APA format

Copy to clipboard

Aničin, L., Stojmenović, M. (2022). Understanding Job Requirements Using Natural Language Processing. Paper presented at Sinteza 2022 - International Scientific Conference on Information Technology and Data Related Research. doi:10.15308/Sinteza-2022-457-463

BibTeX format
Download

RefWorks Tagged format
Download