ct 16(7): e5

Research Article

Eye-tracking Data, Complex Networks and Rough Sets: an Attempt Toward Combining Them

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  • @ARTICLE{10.4108/eai.3-12-2015.2262487,
        author={Boleslaw Jaskula and Jaroslaw Szkola and Krzysztof Pancerz and Aneta Derkacz},
        title={Eye-tracking Data, Complex Networks and Rough Sets: an Attempt Toward Combining Them},
        journal={EAI Endorsed Transactions on Creative Technologies},
        volume={3},
        number={7},
        publisher={ACM},
        journal_a={CT},
        year={2016},
        month={5},
        keywords={eye-tracking, complex networks, rough sets},
        doi={10.4108/eai.3-12-2015.2262487}
    }
    
  • Boleslaw Jaskula
    Jaroslaw Szkola
    Krzysztof Pancerz
    Aneta Derkacz
    Year: 2016
    Eye-tracking Data, Complex Networks and Rough Sets: an Attempt Toward Combining Them
    CT
    EAI
    DOI: 10.4108/eai.3-12-2015.2262487
Boleslaw Jaskula1, Jaroslaw Szkola1, Krzysztof Pancerz2,*, Aneta Derkacz3
  • 1: University of Information Technology and Management in Rzeszow, Poland
  • 2: Univeristy of Rzeszow, Poland and University of Information Technology and Management in Rzeszow, Poland
  • 3: University of Management and Administration in Zamosc, Poland
*Contact email: kkpancerz@gmail.com

Abstract

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 sacade connections between object components identified in visual stimuli used in eye-tracking experiments. Theoretical foundations given in the paper are supplemented with a numerical example explaining the proposed approach.