A Framework for e-Recruitment Recommender Systems

Página do item simplificado
dc.contributor.authorFreire M.N.
dc.contributor.authorCastro L.N.
dc.date.accessioned2024-03-12T23:49:28Z
dc.date.available2024-03-12T23:49:28Z
dc.date.issued2020
dc.description.abstract© 2020, Springer Nature Switzerland AG.e-Recruitment Recommender Systems have been attracting attention over the last few years. It is an economically relevant field and can potentially revolutionize how organizations execute talent search and acquisition. This paper briefly discusses the e-Recruitment problem and presents a framework together with three recommendation models aiming to overcome the particular challenges presented in this field.
dc.description.firstpage165
dc.description.lastpage175
dc.description.volume12416 LNAI
dc.identifier.doi10.1007/978-3-030-61534-5_15
dc.identifier.issn1611-3349
dc.identifier.urihttps://dspace.mackenzie.br/handle/10899/35064
dc.relation.ispartofLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.rightsAcesso Restrito
dc.subject.otherlanguagee-Recruitment
dc.subject.otherlanguageFramework
dc.subject.otherlanguageRecommender system
dc.titleA Framework for e-Recruitment Recommender Systems
dc.typeArtigo de evento
local.scopus.citations1
local.scopus.eid2-s2.0-85096615285
local.scopus.updated2024-05-01
local.scopus.urlhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85096615285&origin=inward
Arquivos
Coleções
Artigo de evento