| Popis: |
With the increase of competitiveness among companies, knowledge management has become a strategic factor to ensure the sustainability of organizations. One of the most challenging problems within knowledge management is the representation of tacit knowledge, the subjective specialty, and the skills of a professional team. Many approaches have been proposed to store, represent, and retrieve tacit knowledge, but most fail on providing a sustainable and adaptable solution. In this paper, this problem was addressed by proposing a Growing Hierarchical Self-Organizing Map neural network to map the tacit knowledge from an organization in an unsupervised and hierarchical manner. It was introduced a novel relevance gain function, to process symbolic data, and find that our neural network can model the tacit knowledge of a real business. |
