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Integrating Click-Through and Eye-Tracking Logs for Decision-Making Process Mining


  • Razvan PETRUSEL



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 be traced using two means: mouse tracing (i.e. clicks) and eye-tracking (i.e. eye fixations). Then, we discuss a mining approach, based on the log, which extracts a Decision Data Model (DDM). We use the DDM to determine, post-hoc, which decision strategy was employed. The paper concludes with a validation based on a controlled experiment.

Suggested Citation

  • Razvan PETRUSEL, 2014. "Integrating Click-Through and Eye-Tracking Logs for Decision-Making Process Mining," Informatica Economica, Academy of Economic Studies - Bucharest, Romania, vol. 18(1), pages 56-68.
  • Handle: RePEc:aes:infoec:v:18:y:2014:i:1:p:56-68

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    References listed on IDEAS

    1. Loay ALTAMIMI, 2013. "A Lexical Analysis of Social Software Literature," Informatica Economica, Academy of Economic Studies - Bucharest, Romania, vol. 17(1), pages 14-26.
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