Enabling semantic analysis of user browsing patterns in the web of data

A useful step towards better interpretation and analysis of the usage patterns is to formalize the semantics of the re-sources that users are accessing in the Web. We focus on this problem and present an approach for the semantic for-malization of usage logs, which lays the basis for effective techniques of querying expressive usage patterns. We also present a query answering approach, which is useful to find in the logs expressive patterns of usage behavior via formu-lation of semantic and temporal-based constraints. We have processed over 30 thousand user browsing sessions extracted from usage logs of DBPedia and Semantic Web Dog Food. The logs are semantically formalized using re-spective domain ontologies and RDF representations of the Web resources being accessed. We show the effectiveness of our approach through experimental results, providing in this way an exploratory analysis of the way users browse the Web of Data