Author:
Conati Cristina,Carenini Giuseppe,Toker Dereck,Lallé Sébastien
Abstract
This paper summarizes an ongoing multi-year project aiming to uncover knowledge and techniques for devising intelligent environments for user-adaptive visualizations. We ran three studies designed to investigate the impact of user and task characteristics on user performance and satisfaction in different visualization contexts. Eye-tracking data collected in each study was analyzed to uncover possible interactions between user/task characteristics and gaze behavior during visualization processing. Finally, we investigated user models that can assess user characteristics relevant for adaptation from eye tracking data.
Publisher
Association for the Advancement of Artificial Intelligence (AAAI)
Cited by
8 articles.
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