Enabling Semantic Analysis of User Browsing Patterns in the Web of Data
This work addresses the need for better analysis of user behavior in semantic web environments, though it appears incremental by building on existing semantic formalization techniques.
The paper tackles the problem of interpreting user browsing patterns in the Web of Data by formalizing the semantics of usage logs, enabling querying of expressive patterns with semantic and temporal constraints. It processed over 30,000 user sessions from DBPedia and Semantic Web Dog Food, showing effectiveness through experimental results.
A useful step towards better interpretation and analysis of the usage patterns is to formalize the semantics of the resources that users are accessing in the Web. We focus on this problem and present an approach for the semantic formalization of usage logs, which lays the basis for eective techniques of querying expressive usage patterns. We also present a query answering approach, which is useful to nd in the logs expressive patterns of usage behavior via formulation 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. All these events are formalized semantically using respective domain ontologies and RDF representations of the Web resources being accessed. We show the eectiveness of our approach through experimental results, providing in this way an exploratory analysis of the way users browse theWeb of Data.