Career-path analysis using drifting Markov models DMM and self-organizing mapsReport as inadecuate




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1 CES - Centre d-économie de la Sorbonne 2 SAMM - Statistique, Analyse et Modélisation Multidisciplinaire SAmos-Marin Mersenne 3 CEREQ - Centre d-études et de recherches sur les qualifications

Abstract : Analyzing school-to-work transitions is an important challenge for the specialists of the labor-market. The aim of this paper is to study the insertion of graduates and to identify the main career-paths typologies. We introduce a new methodology for clustering career-paths by combining statistical estimation of non-homogeneous Markov chains with self-organizing maps. The proposed methodology is tested on real-life data issued from the survey -Generation 98- elaborated by CEREQ, France http:-www.cereq.fr-

keyword : Career paths categorical data drifting Markov model self organizing maps





Author: Sébastien Massoni - Madalina Olteanu - Patrick Rousset -

Source: https://hal.archives-ouvertes.fr/



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