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Career-path analysis using drifting Markov models (DMM) and self-organizing maps

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/)
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https://hal.archives-ouvertes.fr/hal-00443530
Contributor : Madalina Olteanu <>
Submitted on : Wednesday, December 30, 2009 - 6:55:34 AM
Last modification on : Tuesday, January 19, 2021 - 11:08:38 AM
Long-term archiving on: : Friday, June 18, 2010 - 12:10:00 AM

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Sébastien Massoni, Madalina Olteanu, Patrick Rousset. Career-path analysis using drifting Markov models (DMM) and self-organizing maps. MASHS, 2010, Lille, France. ⟨hal-00443530⟩

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