Semantic Navigation Maps for Information Agents in Environment Information Systems

The automated retrieval of information in Environment Information Systems by information agents is severely hindered by the heterogeneity of these systems. For the decision if an information is a relevant answer to a query, information agents need to understand semantics and context of the query. In this paper we propose our concept of describing and exploiting contextual relations in the domain of environment information on the base of Kohonen’s self-organizing feature maps. We apply this concept for the automated semantic classification of query results into an existing knowledge space. Using this technique, information agents can be endowed with domain knowledge. Thus they are enabled to retrieve information in heterogeneous Environment Information Systems matching the context of the query.