Abels, StephanGreven, ChristophValdez, André CaleroSchroeder, UlrikZiefle, MartinaWeyers, BenjaminDittmar, Anke2017-06-172017-06-172016https://dl.gi.de/handle/20.500.12116/333Digital libraries are becoming larger, while suffering from inefficient interfaces and search patterns. Recommender Systems are a sensible and important service for users of digital libraries. The aim of recommender systems is to reduce cognitive effort, simplify search and to embed results in a larger context. In this article we compare to recommender systems – the Action Science Explorer and Papercube. Both systems are used to recommend scientific literature and use graph-based approaches. From user studies we derive the need for research to understand complexity of graphs.enText/Conference Paper10.18420/muc2016-ws11-0005