Semantic Matchmaking for Location-Aware Ubiquitous Resource Discovery

Semantic technologies can increase effectiveness of resource discovery in mobile environments. Nevertheless, a full exploitation is currently braked by limitations in stability of data links and in availability of computation/memory capabilities of involved devices. This paper presents a platform-independent mobile semantic discovery framework as well as a working prototypical implementation, enabling advanced knowledge-based services taking into account user’s location. The approach allows to rank discovered resources based on a combination of their semantic similarity with respect to the user request and their geographical distance from the user itself, also providing a logic-based explanation of outcomes. A distinguishing feature is that the presented mobile decision support tool can be proficiently exploited by a nontechnical user thanks to careful selection of features, GUI design and optimized implementation. The proposed approach is clarified and motivated in a ubiquitous tourism case study. Performance evaluations are presented to prove its feasibility and usefulness.