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dc.contributor.authorSáiz Bárcena, Lourdes
dc.contributor.authorPérez Pulido, Arturo
dc.contributor.authorHerrero Cosío, Álvaro 
dc.contributor.authorCorchado Rodríguez, Emilio Santiago 
dc.date.accessioned2017-09-06T09:14:35Z
dc.date.available2017-09-06T09:14:35Z
dc.date.issued2011
dc.identifier.citationIntelligent Data Engineering and Automated Learning - IDEAL 2011 Lecture Notes in Computer Science. Lecture Notes in Computer Science. Volumen 6936, pp. 463-473.
dc.identifier.isbn978-3-642-23877-2 (Print) / 978-3-642-23878-9 (Online)
dc.identifier.issn0302-9743 (Print) / 1611-3349 (Online)
dc.identifier.urihttp://hdl.handle.net/10366/134893
dc.description.abstractThis study presents the application of an unsupervised neural projection model for the analysis of Human Resources (HR) from a Knowledge Management (KM) standpoint. This work examines the critical role that the acquisition and retention of specialized employees play in Hi-tech companies, particularly following the configuration approach of Strategic HR Management. From the projections obtained through the connectionist models, experts in the field may extract conclusions related to some key factors of the HR Management. One of the main goals is to deploy improvement and efficiency actions in the implantation and execution of the HR practices in firms. The proposal is validated by means of an empirical study on a real case study related to the Spanish Hi-tech sector.
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherSpringer Science + Business Media
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Unported
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/3.0/
dc.subjectComputer Science
dc.titleAnalyzing Key Factors of Human Resources Management
dc.typeinfo:eu-repo/semantics/conferenceObject
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess


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