The adaptation of visual search to utility, ecology and design. Issue 80 (August 2015)

• Record Type: Journal Article
• Authors: Tseng, Yuan-Chi; Howes, Andrew
• Is Part Of: International journal of human-computer studies. Issue 80(2015)
• Page Start: 45
• Page End: 55
• Publication Date: 2015-08
• Subjects: Image search -- Strategic adaptation -- Utility maximization -- Ecology -- Information design -- Eye movements; Human-machine systems -- Periodicals; Systems engineering -- Periodicals; Human engineering -- Periodicals; Human engineering; Human-machine systems; Systems engineering; Periodicals; Electronic journals; 004.019
• DOI: 10.1016/j.ijhcs.2015.03.005
• Languages: English
• ISSNs: 1071-5819

Abstract

Abstract: An important question for Human–Computer Interaction is to understand the visual search strategies that people use to scan the results of a search engine and find the information relevant to their current task. Design proposals that support this task include space-filling thumbnails, faceted browsers, and textually enhanced thumbnails, amongst others. We argue that understanding the trade-offs in this space might be informed by a deep understanding of the visual search strategies that people choose given the constraints imposed by the natural ecology of images on the web, the human visual system, and the task demands. In the current paper we report, and empirically evaluate, a computational model of the strategies that people choose in response to these constraints. The model builds on previous insights concerning the human visual system and the adaptive nature of visual search. The results show that strategic parameters, including the number of features to look for, the evaluation-stopping rule, the gaze duration and the number of fixations are explained by the proposed computational model. Highlights: Reports a computational model of eye movements over image search engine results. Reports an empirical study of visual attention for image search engine results. Shows that eye movements are rational given interface design and user priorities. Provides evidence that strategies are adapted to the ecology search engine results.