Situation-Aware Mobile Service Recommendation with Fuzzy Logic and Semantic Web

Today's mobile Internet service portals offer thousands of services and mobile devices can host plenty of applications, documents and web URLs. Hence, for average mobile users there is an increasing cognitive burden in finding the most appropriate service among the many available. On the other hand, methodologies such as bookmarks and resource tagging require a great arranging effort to handle increasing resources. To help mobile users in managing and using this personal information space, new levels of granularity should be introduced in the organization of services, together with some degree of self-awareness. This paper proposes a situation-aware service recommender that helps locating services proactively. In the recommender, a semantic layer determines one or more user current situations by using domain knowledge expressed in terms of ontology and semantic rules. A fuzzy inference layer manages the vagueness of some contextual condition of these rules and outputs an uncertainty degree for each situation. Based on this degree, the recommender proposes a set of specific resources.