2nd Workshop on Engineering Computer-Human Interaction in Recommender Systems (EnCHIReS 2017)
June 26-29, 2017, Lisbon, Portugal

A recommender system suggests items that might be interesting for the users, by analyzing their previous preferences. While these preferences can be explicitly expressed in the form of ratings or likes, the interactions of the users with the system can also be exploited, in order to collect implicit preferences and provide more fine-grained knowledge on what the users are experiencing. Therefore, the user interface engineering community can play a crucial role in the design of more effective recommender systems. Indeed, it is important to move from the perception of a recommender system as a black box that provides suggestions that are not interpretable and are completely disconnected from the user model, since this would lead to a lack of trust of the users in the system. It is also widely-known that a current challenge in the recommender systems research is to go beyond accuracy, since the acceptance of a recommendation by the user is related to a set of other factors, such as the way in which the recommended items are presented to the user. Therefore, an analysis of the capability of the user interface to improve both the effectiveness and the understanding of the recommendations is an aspect of central interest in this research area.

Papers primarily based on (but not limited to) the following topics are welcome: (Topics include but not limited to)