To support the sharing and reusing of well-defined knowledge among knowledge management systems, it is useful to use standardised formalisation. It is also common effort to difficulty of knowledge acquisition known as knowledge acquisition bottleneck. In this paper investigates the feasibility of using techniques in case-based reasoning of artificial intelligence for the knowledge acquisition phase in knowledge management systems. The need of an ontological approach of the semantic web for well-defined set of domain knowledge is proposed in order to avoid knowledge acquisition bottleneck. Our viewpoint of this approach is that the ontology-driven mechanism allows us to provide standardised structured vocabularies and conceptualisation of knowledge domain. Over the standardised platform, we see an alternative to share and reuse homogenous information and knowledge in the knowledge management systems.
Kang, S. & Lau, S. K. (2003). A framework for case-based reasoning integration on knowledge management systems. In J. Hanisch, D. Falconer, S. Horrocks & M. Hillier (Eds.), 7th Pacific Asia Conference on Information Systems (pp. 1327-1343). Adelaide, SA: University of South Australia.