Different approaches have been used to model contextual information in context-aware systems. Comparing to other models, ontology-based modeling offers more expressiveness, semantically sharing and interoperability. It supports reasoning tasks in a better way than other approaches. However, the main concern with ontology implementation is the expensive computational request for the reasoning process which makes this model unsuitable for critical time application. In tourism domain, using ontology model affects response time which is unacceptable for on-the-move tourists. Late response based on current tourist location might recommend him points of his interest that are already behind him especially when he is riding. In this paper, we propose an approach that uses current user location and speed to provide tourist with a recommendation about points of his interest before reaching them. Besides location and user speed, our approach is aware of network speed as an important factor that affects response time, and consequently impacts calculation of predicted user location.Scopu
