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dc.contributor.authorHerrero Cosío, Álvaro
dc.contributor.authorMata Conde, Aitor
dc.contributor.authorCorchado Rodríguez, Emilio Santiago 
dc.contributor.authorSáiz Bárcena, Lourdes
dc.date.accessioned2017-09-06T09:15:15Z
dc.date.available2017-09-06T09:15:15Z
dc.date.issued2009
dc.identifier.citationHybrid Artificial Intelligence Systems Lecture Notes in Computer Science. Lecture Notes in Computer Science. Volumen 5572, pp. 157-168.
dc.identifier.isbn978-3-642-02318-7 (Print) / 978-3-642-02319-4 (Online)
dc.identifier.issn0302-9743 (Print) / 1611-3349 (Online)
dc.identifier.urihttp://hdl.handle.net/10366/134961
dc.description.abstractThis 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.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.titleA Hybrid Solution for Advice in the Knowledge Management Field
dc.typeinfo:eu-repo/semantics/article
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess


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Attribution-NonCommercial-NoDerivs 3.0 Unported
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