On the improvement of Knowledge Management status through case-based reasoning in a hybrid approach

From an enterprise point of view, Knowledge Management (KM) enables organizations to capture, share, and apply the collective experience and know-how (knowledge) of their staff. Up to now, little effort has been devoted to apply Artificial Intelligent techniques to KM systems. This paper proposes the application of case-based reasoning, in combination with a neural model, to develop a KM system. This combined approach profiles the KM status of the whole organization and automatically generates proposals, aimed at improving the KM situation of organization units. The system is fed with KM data collected at the organization and unit contexts. The 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.