A data-driven approach to automatic extraction of professional figure profiles from Résumés

2Citations
Citations of this article
15Readers
Mendeley users who have this article in their library.
Get full text

Abstract

The process of selecting and interviewing suitable candidates for a job position is time-consuming and labour-intensive. Despite the existence of software applications aimed at helping professional recruiters in the process, only recently with Industry 4.0 there has been a real interest in implementing autonomous and data-driven approaches that can provide insights and practical assistance to recruiters. In this paper, we propose a framework that is aimed at improving the performances of an Applicant Tracking System. More specifically, we exploit advanced Natural Language Processing and Text Mining techniques to automatically profile resources (i.e. candidates for a job) and offers by extracting relevant keywords and building a semantic representation of résumés and job opportunities.

Cite

CITATION STYLE

APA

Bondielli, A., & Marcelloni, F. (2019). A data-driven approach to automatic extraction of professional figure profiles from Résumés. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11871 LNCS, pp. 155–165). Springer. https://doi.org/10.1007/978-3-030-33607-3_18

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free