Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/72264
Title: A job-seeking advisor bot based in data mining
Authors: Rodríguez-Rodríguez, J. C. 
De Blasio , Gabriele Salvatore 
García, C. R. 
Quesada-Arencibia, A. 
UNESCO Clasification: 120312 Bancos de datos
1203 Ciencia de los ordenadores
Keywords: Data mining
Employment portal
Job search
Training
Issue Date: 2020
Journal: Lecture Notes in Computer Science 
Conference: 17th International Conference on Computer Aided Systems Theory, EUROCAST 2019 
Abstract: Promentor is a solution that advises job seekers how to effectively improve their chances of getting a job in a certain area of interest by focusing on what, at least historically, seems to work best. To this end, Promentor first analyzes previous selection processes, trying to quantitatively evaluate the effective value of the characteristics that the candidates put into play in the selection. With this evaluation, Promentor can estimate the value of a profile of the job seeker who requests advice based on the characteristics that make it up. Promentor then makes a simulation by applying each of the suggestions on the job seeker’s profile exhaustively and evaluating the modified profile. In this way, Promentor identifies which suggestions offer the greatest increase in qualification, and are therefore more recommendable. Promentor is a module of the employment web portal GetaJob.es, which has been developed in parallel and equipped with specific capabilities for collecting the data required by Promentor.
URI: http://hdl.handle.net/10553/72264
ISBN: 978-3-030-45092-2
ISSN: 0302-9743
DOI: 10.1007/978-3-030-45093-9_10
Source: Lecture Notes in Computer Science [0302-9743], v. 12013 LNCS, p. 75-82, (Enero 2020)
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