Dealing with Semantic Heterogeneity for Improving Web Usage

Designing applications for supporting user activity on accessing Web information sources is one of the most appealing challenges for researchers in the Artificial Intelligence area. We meet the above goal by proposing an agent-based approach relying on a new model, called concept-graph, capable of representing user-behavior-dependent relationships among concepts and, importantly, dealing with structural and semantic heterogeneity of Web sources. The latter feature is a nice peculiarity of our approach, which witnesses how recent results coming from the Cooperative Information Systems area, can be profitably exploited in the recommender systems field. Finally, in order to test the validity of our approach, we have implemented the proposed framework in a Java prototype.