Eye-tracking sequences can be considered in terms of complex networks. On the basis of complex network representation of eye-tracking data, we define a measure, derived from rough set theory, for assessing the cohesion of saccade connections between object components identified in visual stimuli used in eye-tracking experiments. Rough sets are an appropriate tool to deal with rough (ambiguous, imprecise) concepts. Theoretical foundations given in the paper are supplemented with a numerical example explaining the proposed approach.

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