Job Offer Management: How Improve the Ranking of Candidates

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.
Type de document :
Communication dans un congrès
ISMIS'09: International Symposium on Methodologies for Intelligent Systems, France. pp.431-441, 2009, 〈http://ismis09.vse.cz/〉. 〈10.1007/978-3-642-04125-9_46〉
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-00537101
Contributeur : Nicolas Béchet <>
Soumis le : mercredi 17 novembre 2010 - 15:59:06
Dernière modification le : jeudi 24 mai 2018 - 15:59:23

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Rémy Kessler, Nicolas Béchet, Torres-Moreno Juan-Manuel, 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, 2009, 〈http://ismis09.vse.cz/〉. 〈10.1007/978-3-642-04125-9_46〉. 〈lirmm-00537101〉

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