Abstract
Nowadays, eye tracking data have become important and valuable information that help to understand the behavior of users. The gathering of these data is not an issue anymore. However, the problem is the analysis process and especially how can these raw data be converted to understandable and useful information. Visual analytics can solve this issue by combining human analytics skills and the advanced computer analytics. This leads to the novel discoveries and helps humans take control of the analytical process. These visualizations can be used to solve difficult problems by discovering new unknown patterns of available data. In this work, we discussed different methods that are used in the case of eye tracking data, and we addressed the challenges of visual analytics in this context.
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Quadar, N., Chehri, A., Geon, G. (2021). Visual Analytics Methods for Eye Tracking Data. In: Zimmermann, A., Howlett, R., Jain, L. (eds) Human Centred Intelligent Systems. Smart Innovation, Systems and Technologies, vol 189. Springer, Singapore. https://doi.org/10.1007/978-981-15-5784-2_1
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