Please use this identifier to cite or link to this item: http://elea.unisa.it/xmlui/handle/10556/6434
Title: Corporate profiling: text analytics for employability skills mining
Authors: Smaldone, Francesco
Antonelli, Valerio
Pellicano, Marco
Keywords: Big data analytics;Corporate profiling;Text mining
Issue Date: 2-Nov-2021
Publisher: Universita degli studi di Salerno
Abstract: In the current scenario, the increasing attention to big data realities is causing firms to develop new tools for corporate management, touching several realities from the marketing compart to the HR management. In the context of today’s rapid technological development and its application in a growing array of fields, the role of big data is simultaneously evolving. The present doctoral thesis provides insights into the current expectations of employers seeking to hire individuals. Profiling was conducted by harvesting relevant data from job ads published in a US employment website, which currently attracts the US market's highest recruitment traffic. This research aims to identify the skills, experience, and qualifications sought by employers in several industries and for several professionals, also indicating to candidates the tangible parameters that would increase their employability in such a role. [edited by Author]
Description: 2019 - 2020
URI: http://elea.unisa.it:8080/xmlui/handle/10556/6434
http://dx.doi.org/10.14273/unisa-4506
Appears in Collections:Big Data Management

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tesi di dottorato F. Smaldone.pdftesi di dottorato20 MBAdobe PDFView/Open
abstract in inglese e in italiano F. Smaldone.pdfabstract in italiano e in inglese a cura dell'Autore135,25 kBAdobe PDFView/Open


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