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In current software every click of the users is logged, therefore a wealth of click-through information exists. Besides, recent technologies have made eye-tracking affordable and an alternative to other human-computer interaction means (e.g. mouse, touchscreens). A big challenge is to make sense of all this data and convert it into useful information. This paper introduces a possible solution placed in the context of decision-making processes. We show how the decision maker's activity can bedoi:10.12948/issn14531305/18.1.2014.05 fatcat:ez7dtbkg4jbmfg64iksyzj3tvq