By: Alberto J. Cañas & Marco Carvalho
Institute for Human & Machine Cognition
Pensacola, FL 32502
Concept maps are a graphical representation of a person’s (or group of persons’) understanding of a domain. As such, it can be considered a knowledge representation scheme. However, the Artificial
Intelligence (AI) community frowns on the use of the term “knowledge representation” to refer to concept maps, because they cannot be readily translated to a formal representation for inference or other AI techniques. In this paper we propose that despite the free-style format that concept maps can take, specific
characteristics of well-constructed concept maps (structure, semantics, context, etc.) provide an abundance of information on which to develop smart tools that aid the user in the process of constructing concept maps. Our claim is that the compromise in the formalism in lieu of flexibility proposed by concept maps can be compensated, with the help of AI and smart tools, to help bring the best of both worlds to knowledge elicitation and representation. We demonstrate this argument with a set of smart tools that have been implemented in the CmapTools software kit.