Hybrid recommender system for context-aware recommendations of mobile applications

The goal of the work in this paper is towards the incorporation of context in recommender systems in the domain of mobile applications. The approach recommends mobile applications to users based on what other users have installed in a similar context. The idea is to apply a hybrid recommender system to deal with the added complexity of context. We have designed and realized the application to test our ideas. Users can select among several content-based or collaborative filtering components, including a rule-based module using information on point-of-interests in the vicinity of the user, and a component for the integration of traditional collaborative filtering. The implementation is integrated in a framework supporting the development and deployment of mobile services.