Hypermedia navigation support by fuzzy logic and neural networks

A system architecture for hypermedia applications is introduced that includes fuzzy logic and artificial neural networks (ANNs) for dynamically creating user-specific paths through a database of multimedia objects. A semantic data model is involved to describe the objects´ characteristics. Fuzzy rules represent pedagogical knowledge whereas ANNs represent experiences and decisions of former users. During a session, the fuzzy rules and ANNs are used by a run-time controller in order to retrieve objects, which are appropriate candidates for continuing the way in the hypermedia network. This framework for navigation in hypermedia databases aims at increasing flexibility to adapt to each user´s preferences, motivation and experiences