Add to ORKGAbstract. In this paper, we discuss an approach to collect data on instances of user confusion during visualization processing. The long-term goal is to use this data to train classifiers that can detect instances of user confusion in real time, as triggers for adaptive interventions aimed at alleviating the confusion.
htmlabstractSupervised Machine Learning techniques can automatically extract information from a vari...
Adaptive visualizations reduces the required cognitive effort to comprehend interactive visual pictu...
A user-adaptive information visualization system capable of learning models of users and the visuali...
Human access to the increasing amount of information and data plays an essential role for the profes...
Classifiers are applied in many domains where classification errors have significant implications. H...
Adaptive visualizations support users in information acquisition and exploration and therewith in hu...
Classifiers are applied in many domains where classification errors have significant implications. H...
Machine Learning techniques can automatically extract information from a variety of multimedia sourc...
This paper summarizes an ongoing multi-year project aiming to uncover knowledge and techniques for d...
A user-adaptive information visualization system capable of learning models of users and the visuali...
Research on incidence of and changes in confusion during complex learning and problem-solving calls ...
Adaptive visualizations reduces the required cognitive effort to comprehend interactive visual pictu...
htmlabstractSupervised Machine Learning techniques can automatically extract information from a vari...
Adaptive visualizations reduces the required cognitive effort to comprehend interactive visual pictu...
A user-adaptive information visualization system capable of learning models of users and the visuali...
Human access to the increasing amount of information and data plays an essential role for the profes...
Classifiers are applied in many domains where classification errors have significant implications. H...
Adaptive visualizations support users in information acquisition and exploration and therewith in hu...
Classifiers are applied in many domains where classification errors have significant implications. H...
Machine Learning techniques can automatically extract information from a variety of multimedia sourc...
This paper summarizes an ongoing multi-year project aiming to uncover knowledge and techniques for d...
A user-adaptive information visualization system capable of learning models of users and the visuali...
Research on incidence of and changes in confusion during complex learning and problem-solving calls ...
Adaptive visualizations reduces the required cognitive effort to comprehend interactive visual pictu...
htmlabstractSupervised Machine Learning techniques can automatically extract information from a vari...
Adaptive visualizations reduces the required cognitive effort to comprehend interactive visual pictu...
A user-adaptive information visualization system capable of learning models of users and the visuali...