Rating support interfaces to improve user experience and recommender accuracy

Authors:
Tien T. Nguyen;Daniel Kluver;Ting-Yu Wang;Pik-Mai Hui;Michael D. Ekstrand;Martijn C. Willemsen;John Riedl
Affiliations:
University of Minnesota, Minneapolis, USA;University of Minnesota, Minneapolis, USA;University of Minnesota, Minneapolis, USA;University of Minnesota, Minneaplis, USA;University of Minnesota, Minneapolis, USA;Eindhoven University of Technology, Eindhoven, Holland;University of Minnesota, Minneapolis, USA
Venue:
Proceedings of the 7th ACM conference on Recommender systems
Year:
2013

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Abstract

One of the challenges for recommender systems is that users struggle to accurately map their internal preferences to external measures of quality such as ratings. We study two methods for supporting the mapping process: (i) reminding the user of characteristics of items by providing personalized tags and (ii) relating rating decisions to prior rating decisions using exemplars. In our study, we introduce interfaces that provide these methods of support. We also present a set of methodologies to evaluate the efficacy of the new interfaces via a user experiment. Our results suggest that presenting exemplars during the rating process helps users rate more consistently, and increases the quality of the data.