A new optimized machine learning approach for extraction and classification of informations in curriculum vitae

SAFIA BAALI; HICHAM MOUTACHAOUEK; ABDELAZIZ MARZAK; IBRAHIM HAMZANE

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A new optimized machine learning approach for extraction and classification of informations in curriculum vitae

Author(s)

SAFIA BAALI LTIM Laboratory, Ben M'Sik Faculy of science, Hassan II University,,Morocco

HICHAM MOUTACHAOUEK Strectural Engineering,Inteligent Systems, and Electrical Energy, ENSAM,Morocco

ABDELAZIZ MARZAK LTIM Laboratory, Ben M'Sik Faculy of science, Hassan II University,,Morocco

IBRAHIM HAMZANE LTIM Laboratory, Ben M'Sik Faculy of science, Hassan II University,,Morocco

Abstract

The hiring process has evolved It refers to the process of finding, selecting and recruiting new employees to a company/organisation through CVs. We have presented in this paper a solution in the form of an automated and flexible system to extract vital information from unstructured CVs and transform it into a structured format and then use it in a recommendation system according to the available positions.

Publication Details

Page(s) 2051-2067

DOI DOI not available

Published Journal: Journal of Theoretical and Applied Information Technology, Volume: 100, Issue: 7, Year: 2022

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Keywords

Information Extraction, NLP, Machine learning, Recommendation System

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