Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/70819
Campo DC Valoridioma
dc.contributor.authorRodríguez Rodríguez, José Carlosen_US
dc.contributor.authorDe Blasio , Gabriele Salvatoreen_US
dc.contributor.authorGarcía Rodríguez, Carmelo Rubénen_US
dc.contributor.authorQuesada Arencibia, Francisco Alexisen_US
dc.date.accessioned2020-03-10T14:28:13Z-
dc.date.available2020-03-10T14:28:13Z-
dc.date.issued2019en_US
dc.identifier.isbn978-3-030-45096-0en_US
dc.identifier.urihttp://hdl.handle.net/10553/70819-
dc.description.abstractPromentor is a solution that advises jobseekers on how to effectively improve their chances of obtaining employment in a specific field by focusing on what, at least historically, seems to have produced the best results. First, Promentor analyses previous selection processes to quantitatively evaluate the value of the information provided by the candidates during the process. Promentor uses this evaluation to assess the value of the profile of the jobseeker who is requesting advice based on the information it contains. It then conducts a simulation by applying each suggestion to the profile and evaluating the results. In this way, it identifies which suggestions improve the profile the most. Promentor is a module on the GetaJob.es employment website, which was developed in parallel and equipped with specific capabilities for capturing the data that Promentor requires.en_US
dc.languageengen_US
dc.publisherUniversidad de Las Palmas de Gran Canaria (ULPGC)en_US
dc.sourceEUROCAST 2019. Computer Aided Systems Theory. Extended abstracts / Alexis Quesada-Arencibia; José Carlos Rodríguez; Roberto Moreno-Díaz; Roberto Moreno-Díaz jr.; Gabriel de Blasio; Carmelo Rubén García (eds.), p. 27-28en_US
dc.subject1203 Ciencia de los ordenadoresen_US
dc.subject.otherData miningen_US
dc.subject.otherJob searchen_US
dc.subject.otherEmployment websiteen_US
dc.subject.otherTrainingen_US
dc.titlePromentor - Data mining applied to job searchen_US
dc.typeinfo:eu-repo/semantics/conferenceObjecten_US
dc.typeconferenceObjecten_US
dc.relation.conferenceInternational Conference on Computer Aided Systems Theory (EUROCAST 2019)en_US
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Actas de congresosen_US
dc.utils.revisionen_US
dc.identifier.ulpgcen_US
dc.contributor.buulpgcBU-INFen_US
item.fulltextCon texto completo-
item.grantfulltextopen-
crisitem.event.eventsstartdate17-02-2019-
crisitem.event.eventsenddate22-02-2019-
crisitem.author.deptGIR IUCES: Computación inteligente, percepción y big data-
crisitem.author.deptIU de Cibernética, Empresa y Sociedad (IUCES)-
crisitem.author.deptDepartamento de Informática y Sistemas-
crisitem.author.deptGIR IUCES: Computación inteligente, percepción y big data-
crisitem.author.deptIU de Cibernética, Empresa y Sociedad (IUCES)-
crisitem.author.deptDepartamento de Informática y Sistemas-
crisitem.author.deptGIR IUCES: Computación inteligente, percepción y big data-
crisitem.author.deptIU de Cibernética, Empresa y Sociedad (IUCES)-
crisitem.author.deptDepartamento de Informática y Sistemas-
crisitem.author.deptGIR IUCES: Computación inteligente, percepción y big data-
crisitem.author.deptIU de Cibernética, Empresa y Sociedad (IUCES)-
crisitem.author.deptDepartamento de Informática y Sistemas-
crisitem.author.orcid0000-0003-2186-3094-
crisitem.author.orcid0000-0002-6233-567X-
crisitem.author.orcid0000-0003-1433-3730-
crisitem.author.orcid0000-0002-8313-5124-
crisitem.author.parentorgIU de Cibernética, Empresa y Sociedad (IUCES)-
crisitem.author.parentorgIU de Cibernética, Empresa y Sociedad (IUCES)-
crisitem.author.parentorgIU de Cibernética, Empresa y Sociedad (IUCES)-
crisitem.author.parentorgIU de Cibernética, Empresa y Sociedad (IUCES)-
crisitem.author.fullNameRodríguez Rodríguez, José Carlos-
crisitem.author.fullNameDe Blasio, Gabriele Salvatore-
crisitem.author.fullNameGarcía Rodríguez, Carmelo Rubén-
crisitem.author.fullNameQuesada Arencibia, Francisco Alexis-
Colección:Actas de congresos
miniatura
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