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dc.contributor.author | Herrero Cosío, Álvaro | |
dc.contributor.author | Mata Conde, Aitor | |
dc.contributor.author | Corchado Rodríguez, Emilio Santiago | |
dc.contributor.author | Sáiz Bárcena, Lourdes | |
dc.date.accessioned | 2017-09-06T09:15:15Z | |
dc.date.available | 2017-09-06T09:15:15Z | |
dc.date.issued | 2009 | |
dc.identifier.citation | Hybrid Artificial Intelligence Systems Lecture Notes in Computer Science. Lecture Notes in Computer Science. Volumen 5572, pp. 157-168. | |
dc.identifier.isbn | 978-3-642-02318-7 (Print) / 978-3-642-02319-4 (Online) | |
dc.identifier.issn | 0302-9743 (Print) / 1611-3349 (Online) | |
dc.identifier.uri | http://hdl.handle.net/10366/134961 | |
dc.description.abstract | This paper presents a hybrid artificial intelligent solution that helps to automatically generate proposals, aimed at improving the internal states of organization units from a Knowledge Management (KM) point of view. This solution is based on the combination of the Case-Based Reasoning (CBR) and connectionist paradigms. The required outcome consists of customized solutions for different areas of expertise related to the organization units, once a lack of knowledge in any of those has been identified. On the other hand, the system is fed with KM data collected at the organization and unit contexts. This solution has been integrated in a KM system that additionally profiles the KM status of the whole organization. | |
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 | A Hybrid Solution for Advice in the Knowledge Management Field | |
dc.type | info:eu-repo/semantics/article | |
dc.rights.accessRights | info:eu-repo/semantics/openAccess |
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