Abstract
Identifying and using the information from distributed and heterogeneous information sources is a challenging task in many application fields. Even with services that offer well-defined structured content, such as digital libraries, it becomes increasingly difficult for a user to find the desired information. To cope with an overloaded information space, we propose a novel approach - VizRec - combining recommender systems (RS) and visualizations. VizRec suggests personalized visual representations for recommended data. One important aspect of our contribution and a prerequisite for VizRec are user preferences that build a personalization model. We present a crowd based evaluation and show how such a model of preferences can be elicited.
Original language | English |
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Title of host publication | Proceedings of the 20th International Conference on Intelligent User Interfaces Companion |
Pages | 49-52 |
Number of pages | 4 |
Publication status | Published - 2015 |