Combining Fuzzy Logic and Semantic Web to Enable Situation-Awareness in Service Recommendation

Mobile Internet is rapidly growing and an enormous quantity of resources are currently available. Thus, the common mechanisms used up to now to locate resources, such as browsing and searching, do not look anymore to be effective in helping users in mobility. Indeed, the user’s personal information space can be very large, with respect to the limited interaction capabilities of mobile devices. This paper proposes a situation-aware framework for providing personalized resources in a proactive manner. Current situations of the user are inferred by exploiting domain knowledge expressed in terms of ontologies and semantic rules, which are represented in the well-known Web Ontology Language (OWL) and Semantic Web Rule Language (SWRL), respectively. Uncertainty in some contextual rule conditions is handled by defining appropriate linguistic variables through the Fuzzy Control Language (FCL), a standard representation of fuzzy systems for data exchange among different implementations, and adopting a purposely-adapted coding of ontologies and rules. Uncertain conditions bring to infer more than one situation with different certainty degrees: these degrees are used to assign a rank to concurrent situations. Finally, situations are connected to a set of related resources to be recommended to the user.