Personalized recommender system for resource sharing based on context-aware in ubiquitous environments

In ubiquitous environments, user wants to get a variety of services using only his individual device. For this requirement, resource sharing and its efficient processing is one of the new research topics. However, the situations of each user are different and user preferences also are various even if user environments are the same. Therefore, although users want to get the same service in the same space, the most suitable resources for the service are different for all users. In this paper, we propose the personalized resource recommender system which recommends resources inferred by applying user preference and situation. The recommender system uses ontology-based reasoning and rule-based reasoning for being aware of situation and for recommending personalized resources respectively.