Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Frequency analysis of task evoked pupillary response and eye-movement
Proceedings of the 2004 symposium on Eye tracking research & applications
Combining eye movements and collaborative filtering for proactive information retrieval
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Detecting low usability web pages using quantitative data of users' behavior
Proceedings of the 28th international conference on Software engineering
An introduction to ROC analysis
Pattern Recognition Letters - Special issue: ROC analysis in pattern recognition
Estimation of certainty for responses to multiple-choice questionnaires using eye movements
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Identifying web usability problems from eye-tracking data
BCS-HCI '07 Proceedings of the 21st British HCI Group Annual Conference on People and Computers: HCI...but not as we know it - Volume 1
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To estimate viewer's contextual understanding, features of their eye-movements while viewing question statements in response to definition statements, and features of correct and incorrect responses were extracted and compared. Twelve directional features of eye-movements across a two-dimensional space were created, and these features were compared between correct and incorrect responses. The procedure of estimating the response was developed with Support Vector Machines, using these features. The estimation performance and accuracy were assessed across combinations of features. The number of definition statements, which needed to be memorized to answer the question statements during the experiment, affected the estimation accuracy. These results provide evidence that features of eye-movements during reading statements can be used as an index of contextual understanding.