Expressive power of Topic Maps, commonly perceived as method for indexing of information resources, places the standard very close to artificial intelligence and knowledge modelling. Topic Maps resemble semantic networks and conceptual graphs, but offer more - a unique, standards-based way of encoding and exchange of the knowledge.

Starting from description of similarities and differences between artificial intelligence and Topic Maps, paper demonstrates artificial intelligence features worth incorporating into Topic Maps domain along with practical benefits they provide.

Further on it focuses on applications in information filtering and retrieval using proposed topic-map-defined query language and user profile definition.