RWTH Aachen University
Recommender systems are commonly based on user ratings to generate tailored suggestions to users. Instabilities and inconsistencies in these ratings cause noise reduce the quality of recommendations and decrease the users' trust in the sys-tem. Detecting and addressing these instabilities in ratings is therefore very important. In this paper, the authors investigate the influence of interaction methods on the users' rating behavior as one possible source of noise in ratings. The scenario is a movie recommender for smartphones.