| dc.contributor.author | Sáiz Bárcena, Lourdes | |
| dc.contributor.author | Pérez Pulido, Arturo | |
| dc.contributor.author | Herrero Cosío, Álvaro | |
| dc.contributor.author | Corchado Rodríguez, Emilio Santiago | |
| dc.date.accessioned | 2017-09-06T09:14:35Z | |
| dc.date.available | 2017-09-06T09:14:35Z | |
| dc.date.issued | 2011 | |
| dc.identifier.citation | Intelligent Data Engineering and Automated Learning - IDEAL 2011 Lecture Notes in Computer Science. Lecture Notes in Computer Science. Volumen 6936, pp. 463-473. | |
| dc.identifier.isbn | 978-3-642-23877-2 (Print) / 978-3-642-23878-9 (Online) | |
| dc.identifier.issn | 0302-9743 (Print) / 1611-3349 (Online) | |
| dc.identifier.uri | http://hdl.handle.net/10366/134893 | |
| dc.description.abstract | This 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.mimetype | application/pdf | |
| dc.language.iso | en | |
| dc.publisher | Springer Science + Business Media | |
| dc.rights | Attribution-NonCommercial-NoDerivs 3.0 Unported | |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/3.0/ | |
| dc.subject | Computer Science | |
| dc.title | Analyzing Key Factors of Human Resources Management | |
| dc.type | info:eu-repo/semantics/conferenceObject | |
| dc.rights.accessRights | info:eu-repo/semantics/openAccess | |