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Title:Towards Inferring Web Page Relevance — An Eye-Tracking Study
Author(s):Gwizdka, Jacek; Zhang, Yinglong
Subject(s):information seeking/retrieval
human-computer interaction
Abstract:We present initial results from a project, in which we examined feasibility of inferring web page relevance from eye-tracking data. We conduced a controlled, lab-based Web search experiment, in which participants conducted assigned information search tasks on Wikipedia. We performed analyses of variance as well as employed classification algorithms in order to predict user perceived Web page relevance. Our findings demonstrate that it is feasible to infer document relevance from eye-tracking data on Web pages. The results indicate that eye fixation duration, pupil size and the probability of continuing reading are good predictors of Web page relevance. This work extends results from previous studies of text document search conducted in more constrained environments.
Issue Date:2015-03-15
Publisher:iSchools
Series/Report:iConference 2015 Proceedings
Genre:Conference Poster
Type:Text
Language:English
URI:http://hdl.handle.net/2142/73709
Peer Reviewed:yes
Rights Information:Copyright 2015 is held by the authors. Copyright permissions, when appropriate, must be obtained directly from the authors.
Date Available in IDEALS:2015-03-24


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