Rank Aggregation for Presentation-Centric Preference Estimation

We consider the connection between the recommenda- tions' selection process and the form in which these rec- ommendations are then presented to the users. On the one hand, a user of an e-commerce site typically pro- vides her preferences as a (very rough) weak ordering over a small subset of all the available items. On the other hand, the recommendations selected for a user are presented to her as this or another projection of a strict ordering over the whole space of items. Aiming at bridging the gap between these two properties of the systems, we suggest and evaluate techniques for rank aggregation in this setting.