Skip to Main content Skip to Navigation
Conference papers

Job Offer Management: How Improve the Ranking of Candidates

Rémy Kessler 1 Nicolas Béchet 2 Juan-Manuel Torres-Moreno 1 Mathieu Roche 2 Marc El Bèze 1 
2 TEXTE - Exploration et exploitation de données textuelles
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : The market of online job search sites grows exponentially. This implies volumes of information (mostly in the form of free text) become manually impossible to process. An analysis and assisted categorization seems relevant to address this issue. We present E-Gen, a system which aims to perform assisted analysis and categorization of job offers and of the responses of candidates. This paper presents several strategies based on vectorial and probabilistic models to solve the problem of profiling applications according to a specific job offer. Our objective is a system capable of reproducing the judgement of the recruitment consultant. We have evaluated a range of measures of similarity to rank candidatures by using ROC curves. Relevance feedback approach allows to surpass our previous results on this task, difficult, diverse and higly subjective.
Document type :
Conference papers
Complete list of metadata
Contributor : Nicolas Béchet Connect in order to contact the contributor
Submitted on : Wednesday, November 17, 2010 - 3:59:06 PM
Last modification on : Friday, August 5, 2022 - 3:03:22 PM

Links full text



Rémy Kessler, Nicolas Béchet, Juan-Manuel Torres-Moreno, Mathieu Roche, Marc El Bèze. Job Offer Management: How Improve the Ranking of Candidates. ISMIS'09: International Symposium on Methodologies for Intelligent Systems, France. pp.431-441, ⟨10.1007/978-3-642-04125-9_46⟩. ⟨lirmm-00537101⟩



Record views