Context-Aware Adaptive Recommendation of Resources for Mobile Users in a University Campus

The selection of resources within a university campus is not an easy task, due the multitude of physical and virtual resources available. By this fact, a person can easily select a set of resources that cannot attend their needs and interests in the best way. Such multitude of resources can leads to the problem of the person cognitive overload, which happens during the resources selection. This paper presents a novel recommender approach as an alternative to select such best set of resources and avoid the person cognitive overload during it. Due to specificities for recommending learning resources, a knowledge-based approach seems to be more effective to this task and take the context in consideration can help in selecting the best resources to the current user situation. Take in consideration an adaptive interface makes the recommendations non-intrusive and help the user to see the location of the resources in the environment. To validate our approach we are developing a system to be used in an application scenario presented in this paper.