EHCI 2017 - Workshop on Engineering Human-Computer Interaction in Recommender Systems

Recommender systems are widely used in different interactive applications in order to support the users in exploring items that would be interesting for them. In order to provide such suggestions, recommender systems build an internal representation of the current user according her explicit feedback on the items, such as completing the order of a product. While it has been recognized in literature that such preferences express only extreme ratings (either positive or negative), exploiting implicit feedback is still a challenge in engineering user interfaces. In addition, such systems would benefit from the user's inspection in terms of trust and from the user's control in terms of precision. Different solutions have been discussed to these problems in literature, but a general solution is still lacking and engineering such kind of interfaces is still a challenge. In this workshop, we aim to collect novel ideas in this field and to connect the different researchers working in this area.