Concept-Guided Query Expansion for Knowledge Management with Semi-Automatic Knowledge Capturing

In the knowledge economic era, enterprises have realized the importance of knowledge assets and endeavored to think how to improve their competitive abilities by managing and using knowledge assets effectively in the fast-changing environment. The usability of knowledge is limited due to its difficult access, sharing and visualization; however knowledge management systems (KMS) have proven to be efficient and effective in organizing knowledge of high complexity and in large amounts. Despite, the issue of how to effectively retrieve the desired knowledge from vast knowledge bases still remains due to the difficulty to express conceptual ideas with appropriate queries. To tackle this critical matter, we propose a new KMS solution powered by a concept-guided query expansion scheme. In addition, repertory grid analysis is conducted to semi-automatically elicit and model the structure of domain experts' tacit knowledge and build up a hierarchical concept structure. With this mechanism, availability of tacit knowledge is increased and its access and navigation facilitated, allowing users to acquire the desired knowledge and contribute to knowledge dissemination.

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