Using Data from job seekers, job offers and past hirings to learn a Job Recommender System: the VADORE Project

Guillaume Bied (1, 2, 3) , Solal Nathan (3, 2) , Elia Perennes (4, 1) , Christophe Gaillac (5) , Philippe Caillou (3) , Bruno Crépon (1) , Michèle Sebag (6)

1 CREST - Centre de Recherche en Économie et Statistique
2 LISN - Laboratoire Interdisciplinaire des Sciences du Numérique
3 TAU - TAckling the Underspecified
4 Pôle emploi (France)
5 TSE-R - Toulouse School of Economics
6 LMS - Laboratoire de mécanique des solides

The Vador Project started in 2018 between the French Public Employment Service Pole Emploi, computer scientists from Paris Saclay and economist from CREST. The project aims to learn a new recommender system from past hirings and job seekers and offers data. We will present both the past, current and futur research and technical challenges faced by the projects and its contributions.

Domains: Artificial Intelligence [cs.AI]

Guillaume Bied, Solal Nathan, Elia Perennes, Christophe Gaillac, Philippe Caillou, et al.. Using Data from job seekers, job offers and past hirings to learn a Job Recommender System: the VADORE Project. AI for HR and Public Employment Services, Feb 2023, Ghent (BE), Belgium. ⟨hal-04025000⟩