A Knowledge based Navigation System with a Semantic Map Approach

In this paper, we propose a framework based on a sub-symbolic approach for the support of exploratory activities (e.g. learning, training and education) in a hyperspace. By using our framework, it is possible to extract the knowledge on the semantic features of the whole hyperspace and the states of exploratory activities and structure in topological order. This approach is applied to generate the navigation information for the exploratory activity. The space explored is changed automatically by using the knowledge on semantic similarities of the nodes which constitute that space. An extended self-organizing feature map is used as the semantic feature map of the hyperspace, in short Hy -SOM. Hy -SOM is applied to express the user model and generate the navigation strategy for the user. The exploratory history of the user is firstly mapped on the Hy -SOM. Next, the semantic relations between nodes are shown on the map. The result reflects the exploratory state of the user, interpreted with the help of a user model.