Traditional recommender systems usually follow a request-response pattern, i.e. these systems only return item suggestions when a user makes an explicit request. Proactivity means that the system pushes recommendations to the user when the current situation seems appropriate. This is conceivable in mobile scenarios such as restaurant or gas station recommendations. However, proactivity has not gained much attention in recommender system research or has been put into practice. In this paper, we present a new model for proactivity in mobile, context-aware recommender systems. The model relies on domain-dependent context modeling in several categories. We have implemented a prototype gas station recommender and conducted a survey for evaluation. Results showed good correlation of the output of our system with the assessment of users regarding the question when to generate recommendations.     «

Traditional recommender systems usually follow a request-response pattern, i.e. these systems only return item suggestions when a user makes an explicit request. Proactivity means that the system pushes recommendations to the user when the current situation seems appropriate. This is conceivable in mobile scenarios such as restaurant or gas station recommendations. However, proactivity has not gained much attention in recommender system research or has been put into practice. In this paper, we p...     »