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dc.contributor.author | Ruiz, Maria | es_ES |
dc.contributor.author | Igartua, Juan Ignacio | es_ES |
dc.contributor.author | Retegi, Jabier | es_ES |
dc.contributor.author | Uriondo, Aitor | es_ES |
dc.contributor.author | Sudupe, Jose Antonio | es_ES |
dc.contributor.author | Heriz, Izaskun | es_ES |
dc.contributor.author | Garate, Estibaliz | es_ES |
dc.date.accessioned | 2025-01-23T09:05:49Z | |
dc.date.available | 2025-01-23T09:05:49Z | |
dc.date.issued | 2025-01-21 | |
dc.identifier.uri | http://hdl.handle.net/10251/213982 | |
dc.description.abstract | [EN] This research presents the results of a project called EZATECH: Design and development of Artificial Intelligence technologies for knowledge management through the life cycle of workers in organizations , funded by the Basque Government (BG) (Economic Development, Sustainability and Environment Department). The project started in April 2021 and was completed in December 2023. The aim of the study was to develop an architecture to organize and structure knowledge from educational and industrial companies based on the professional profiles that composed the company and the key competencies necessary for the achievement of their organizational objectives. This objective responds to the challenges derived from the existence of a multitude of approaches that have significantly hindered the practical development of Knowledge Management in the business environment: The majority of practical application cases published to date refer to large companies or service companies. Machine Learning, Learning Analytics and People Analytics are the techniques used for the development of the EZATECH architecture, which is a software system to unable Knowledge Management in Educational and Industrial sectors. | es_ES |
dc.description.sponsorship | We would like to thank the Basque Government for their support in the development of this project. Special thanks to the Economic Development, Sustainability and Environment Department. | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | Universitat Politècnica de València | es_ES |
dc.relation.ispartof | Journal of Applied Research in Technology & Engineering | es_ES |
dc.rights | Reconocimiento - No comercial - Compartir igual (by-nc-sa) | es_ES |
dc.subject | Knowledge Management | es_ES |
dc.subject | Education | es_ES |
dc.subject | Industry | es_ES |
dc.subject | Artificial Intelligence | es_ES |
dc.title | EZATECH: Design and development of Artificial Intelligence technologies for knowledge management throughout the life cycle of workers in organizations | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.4995/jarte.2025.21755 | |
dc.rights.accessRights | Abierto | es_ES |
dc.description.bibliographicCitation | Ruiz, M.; Igartua, JI.; Retegi, J.; Uriondo, A.; Sudupe, JA.; Heriz, I.; Garate, E. (2025). EZATECH: Design and development of Artificial Intelligence technologies for knowledge management throughout the life cycle of workers in organizations. Journal of Applied Research in Technology & Engineering. 6(1):24-33. https://doi.org/10.4995/jarte.2025.21755 | es_ES |
dc.description.accrualMethod | OJS | es_ES |
dc.relation.publisherversion | https://doi.org/10.4995/jarte.2025.21755 | es_ES |
dc.description.upvformatpinicio | 24 | es_ES |
dc.description.upvformatpfin | 33 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 6 | es_ES |
dc.description.issue | 1 | es_ES |
dc.identifier.eissn | 2695-8821 | |
dc.relation.pasarela | OJS\21755 | es_ES |
dc.contributor.funder | Eusko Jaurlaritza | es_ES |