Mixed-initiative Recommender Systems: Towards a Next Generation of Recommender Systems through User Involvement
Researchers have become more aware of the fact that effectiveness of recommender systems goes beyond recommendation accuracy. Thus, research on these human factors has gained increased interest, for instance by combining interactive visualisation techniques with recommendation techniques to support transparency and controllability of the recommendation process.
In this talk, I will present our work on interactive visualisations to enable end-users to interact with recommender systems as a means to incorporate user feedback and input and to help them steer this process. In addition, I will present the results of several user studies that investigate how user controllability interacts with different personal characteristics.