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• W2950183257 abstract "We study the problem of inferring readers' identities and estimating their level of text comprehension from observations of their eye movements during reading. We develop a generative model of individual gaze patterns (scanpaths) that makes use of lexical features of the fixated words. Using this generative model, we derive a Fisher-score representation of eye-movement sequences. We study whether a Fisher-SVM with this Fisher kernel and several reference methods are able to identify readers and estimate their level of text comprehension based on eye-tracking data. While none of the methods are able to estimate text comprehension accurately, we find that the SVM with Fisher kernel excels at identifying readers." @default.
• W2950183257 created "2019-06-27" @default.
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• W2950183257 date "2018-09-21" @default.
• W2950183257 modified "2023-10-01" @default.
• W2950183257 title "A Discriminative Model for Identifying Readers and Assessing Text Comprehension from Eye Movements" @default.
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• W2950183257 hasPublicationYear "2018" @default.
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