Supporting configuration choices in smart environments through personalized recommendations

With the increasing availability of smart environments and IoT devices, end-users who might lack specific technical skills are more and more often confronted with configuration tasks. In this paper, we present a prototype we have built to experiment with personalized recommendations as a way to help end-users make configuration choices. On the one hand, it allowed us to test different similarity measures for user models. On the other hand, it offers different recommendation services which can be used to suggest trigger- and action-objects, as well as sample configuration rules.