AI-Powered Curricula Selection: A Neural Network Approach Suited for Small and Medium Companies

Marco Marco (), Paolo Fantozzi (), Luigi Laura () and Antonio Miloso ()
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Marco Marco: International Telematic University Uninettuno
Paolo Fantozzi: Università di Roma “La Sapienza”
Luigi Laura: International Telematic University Uninettuno
Antonio Miloso: International Telematic University Uninettuno

A chapter in Exploring Innovation in a Digital World, 2021, pp 11-20 from Springer

Abstract: Abstract AI and Big Data, in the last years, are changing the business in any aspect. In this paper we deal with the process of curricula selection for small and medium companies, i.e. the so-called last mile of the digitalization. This study proposes a new algorithm that could be integrated into the preliminary CVs screening process carried out by an interviewer in order to assess the right collocation to the skill set of the interviewee for the specific job position. The algorithm analyzes the text of a CV to correctly predict the right job position for the candidate. In particular, we show that with off-the-shelf components it is possible to train and run an artificial neural network suited to support HR in the process of curricula selection.

Keywords: Artificial intelligence; Human resources; Natural language processing (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnichp:978-3-030-87842-9_2

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DOI: 10.1007/978-3-030-87842-9_2

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