A Data-Driven Approach to Automatic Extraction of Professional Figure Profiles from Résumés

  • Alessandro BondielliEmail author
  • Francesco Marcelloni
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11871)


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.



This work was partially supported by Tuscany Region in the context of the project TALENT, “FESR 2014-2020". We wish to thank Dr. Alessio Ciardini, CEO of IT Partner Italia, and Filippo Giunti, IT manager of IT Partner Italia, for providing us with the data and for the invaluable support and insight, both theoretical and practical, on the recruiting field from a company perspective.


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.DINFOUniversity of FlorenceFlorenceItaly
  2. 2.Department of Information EngineeringUniversity of PisaPisaItaly

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