Visual Recommendations for Scientific and Cultural Content

Eduardo Veas, Belgin Mutlu, Cecilia di Sciascio, Gerwald Tschinkel, Vedran Sabol

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review


Supporting individuals who lack experience or competence to evaluate an overwhelming amout of information such as from cultural, scientific and educational content makes recommender system invaluable to cope with the information overload problem. However, even recommended information scales up and users still need to consider large number of items. Visualization takes a foreground role, letting the user explore possibly interesting results. It leverages the high bandwidth of the human visual system to convey massive amounts of information. This paper argues the need to automate the creation of visualizations for unstructured data adapting it to the user's preferences. We describe a prototype solution, taking a radical approach considering both grounded visual perception guidelines and personalized recommendations to suggest the proper visualization.
Original languageUndefined/Unknown
Title of host publicationProceedings of 6th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications
Publication statusPublished - 2015

Cite this