Over the past decade, Information and Communication Technologies (ICT) have revolutionized the job market, including People Recruitment processes that have been completely restructured by AI-based tools and techniques.
So what are the scenarios for HR specialists? And how it becomes possible to perfectly match a given job description with the data contained within the multiple CVs that accumulate every day in the databases of organizations?
The topic was widely discussed and deepened by Alessandro Barducci - R&D Manager of Fiven, and Simone Iannaccone - Solutions Architect of Fiven, in collaboration with the teachers of the Department of Electrical Engineering and Information Technologies of the University of Naples Federico II, within the academic and international publication entitled "An end-to-end framework for information extraction from Italian resumes"
As experts point out, the extraction of information from curricula is often a great challenge because of their high heterogeneity, both in form and style, and because of the lack of shared standards between different companies and countries.
For this reason, Fiven and Research Center of the University of Naples have worked synergistically to develop an innovative end-to-end framework with which it is possible to analyze in a uniform way the data contained in the different CV formats, to organize and segment them in parts semantically consistent thanks to linguistic patterns and keyword matching techniques.
This step is then followed by further processing of the data through an NER algorithm, based on pre-addressed linguistic models able to extrapolate the relevant information to be consulted to verify the suitability of a candidate for a specific job offer.
The article reviews the method of job-fitting developed by the authors, highlighting the advantages of this new segmentation strategy, especially when combined with modern GNP models, compared to standard analytical approaches already existing on the market.
Read the full article at this link: An end-to-end framework for information extraction from Italian resumes - ScienceDirect
Over the past decade, Information and Communication Technologies (ICT) have revolutionized the job market, including People Recruitment processes that have been completely restructured by AI-based tools and techniques.
So what are the scenarios for HR specialists? And how it becomes possible to perfectly match a given job description with the data contained within the multiple CVs that accumulate every day in the databases of organizations?
The topic was widely discussed and deepened by Alessandro Barducci - R&D Manager of Fiven, and Simone Iannaccone - Solutions Architect of Fiven, in collaboration with the teachers of the Department of Electrical Engineering and Information Technologies of the University of Naples Federico II, within the academic and international publication entitled "An end-to-end framework for information extraction from Italian resumes"
As experts point out, the extraction of information from curricula is often a great challenge because of their high heterogeneity, both in form and style, and because of the lack of shared standards between different companies and countries.
For this reason, Fiven and Research Center of the University of Naples have worked synergistically to develop an innovative end-to-end framework with which it is possible to analyze in a uniform way the data contained in the different CV formats, to organize and segment them in parts semantically consistent thanks to linguistic patterns and keyword matching techniques.
This step is then followed by further processing of the data through an NER algorithm, based on pre-addressed linguistic models able to extrapolate the relevant information to be consulted to verify the suitability of a candidate for a specific job offer.
The article reviews the method of job-fitting developed by the authors, highlighting the advantages of this new segmentation strategy, especially when combined with modern GNP models, compared to standard analytical approaches already existing on the market.
Read the full article at this link: An end-to-end framework for information extraction from Italian resumes - ScienceDirect
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