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e-Recrutement : recherche de mots-clés pertinents dans le titre des annonces d'emploi

Abstract : The increase in the number of different ways to recruit online has made the issue of job posting performance and its optimization increasingly important. In particular, performance can be assessed by the amount of applications received. In this paper, the goal is to define a strategy for detecting key-words within a job posting’s title that provide information to explain the posting’s performance. We will work on a corpus of job postings characterized by the underlying function (e.g. marketing, finance,…). After a pre-processing of filtering on the corpus, we will compute characteristic forms and identify the most frequent forms. In order to confirm the relevance of the key-words obtained, the latters are coded into dichotomic variables and introduced as predictors in a regression tree, in addition to function predictors. The results are encouraging and confirm key-words contribution into explaining performance.
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Submitted on : Monday, March 23, 2020 - 10:10:01 AM
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Julie Séguéla, Gilbert Saporta, Stéphane Le Viet. e-Recrutement : recherche de mots-clés pertinents dans le titre des annonces d'emploi. JADT'2010, 10th International Conference on Statistical Analysis of Textual Data, Jun 2010, Rome, Italie. ⟨hal-01125769⟩



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